Overview

Dataset statistics

Number of variables29
Number of observations225272
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory50.1 MiB
Average record size in memory233.0 B

Variable types

Numeric7
DateTime1
Text18
Categorical2
Boolean1

Alerts

incident_url_fields_missing has constant value ""Constant
incident_id has unique valuesUnique
incident_url has unique valuesUnique

Reproduction

Analysis started2023-11-25 21:20:10.949007
Analysis finished2023-11-25 21:20:50.639525
Duration39.69 seconds
Software versionydata-profiling vv4.6.2
Download configurationconfig.json

Variables

incident_id
Real number (ℝ)

UNIQUE 

Distinct225272
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean559445.53
Minimum92114
Maximum1083472
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 MiB
2023-11-25T22:20:50.763085image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum92114
5-th percentile126946.65
Q1308282
median543826
Q3817615.75
95-th percentile1028952.6
Maximum1083472
Range991358
Interquartile range (IQR)509333.75

Descriptive statistics

Standard deviation293320.45
Coefficient of variation (CV)0.52430565
Kurtosis-1.2268838
Mean559445.53
Median Absolute Deviation (MAD)253642
Skewness0.094659662
Sum1.2602741 × 1011
Variance8.6036888 × 1010
MonotonicityNot monotonic
2023-11-25T22:20:50.960432image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
984353 1
 
< 0.1%
721166 1
 
< 0.1%
718029 1
 
< 0.1%
717952 1
 
< 0.1%
719468 1
 
< 0.1%
719472 1
 
< 0.1%
722730 1
 
< 0.1%
718123 1
 
< 0.1%
718096 1
 
< 0.1%
719628 1
 
< 0.1%
Other values (225262) 225262
> 99.9%
ValueCountFrequency (%)
92114 1
< 0.1%
92117 1
< 0.1%
92119 1
< 0.1%
92122 1
< 0.1%
92125 1
< 0.1%
92129 1
< 0.1%
92131 1
< 0.1%
92133 1
< 0.1%
92135 1
< 0.1%
92137 1
< 0.1%
ValueCountFrequency (%)
1083472 1
< 0.1%
1083466 1
< 0.1%
1083457 1
< 0.1%
1083435 1
< 0.1%
1083428 1
< 0.1%
1083413 1
< 0.1%
1083396 1
< 0.1%
1083390 1
< 0.1%
1083389 1
< 0.1%
1083379 1
< 0.1%

date
Date

Distinct1565
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
Minimum2013-05-02 00:00:00
Maximum2018-03-31 00:00:00
2023-11-25T22:20:51.138934image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:51.341492image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

state
Text

Distinct51
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2023-11-25T22:20:51.613513image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length20
Median length13
Mean length8.6784376
Min length4

Characters and Unicode

Total characters1955009
Distinct characters46
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMaryland
2nd rowNew Jersey
3rd rowNew York
4th rowNew York
5th rowNew Jersey
ValueCountFrequency (%)
new 16820
 
6.3%
illinois 16693
 
6.3%
california 15155
 
5.7%
carolina 14745
 
5.5%
florida 13949
 
5.2%
texas 12540
 
4.7%
ohio 9640
 
3.6%
york 9218
 
3.5%
north 8750
 
3.3%
georgia 8376
 
3.1%
Other values (45) 140563
52.8%
2023-11-25T22:20:52.193250image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 240804
12.3%
i 231218
11.8%
n 165413
 
8.5%
o 161117
 
8.2%
s 147019
 
7.5%
e 114910
 
5.9%
r 111704
 
5.7%
l 109289
 
5.6%
t 53483
 
2.7%
h 46767
 
2.4%
Other values (36) 573285
29.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1650475
84.4%
Uppercase Letter 263357
 
13.5%
Space Separator 41177
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 240804
14.6%
i 231218
14.0%
n 165413
10.0%
o 161117
9.8%
s 147019
8.9%
e 114910
7.0%
r 111704
6.8%
l 109289
6.6%
t 53483
 
3.2%
h 46767
 
2.8%
Other values (14) 268751
16.3%
Uppercase Letter
ValueCountFrequency (%)
C 38970
14.8%
M 31815
12.1%
N 28946
11.0%
I 26073
9.9%
T 19727
 
7.5%
O 14980
 
5.7%
F 13949
 
5.3%
A 11102
 
4.2%
W 9706
 
3.7%
Y 9218
 
3.5%
Other values (11) 58871
22.4%
Space Separator
ValueCountFrequency (%)
41177
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1913832
97.9%
Common 41177
 
2.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 240804
12.6%
i 231218
12.1%
n 165413
 
8.6%
o 161117
 
8.4%
s 147019
 
7.7%
e 114910
 
6.0%
r 111704
 
5.8%
l 109289
 
5.7%
t 53483
 
2.8%
h 46767
 
2.4%
Other values (35) 532108
27.8%
Common
ValueCountFrequency (%)
41177
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1955009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 240804
12.3%
i 231218
11.8%
n 165413
 
8.5%
o 161117
 
8.2%
s 147019
 
7.5%
e 114910
 
5.9%
r 111704
 
5.7%
l 109289
 
5.6%
t 53483
 
2.7%
h 46767
 
2.4%
Other values (36) 573285
29.3%
Distinct12273
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2023-11-25T22:20:52.643526image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length46
Median length43
Mean length9.3431496
Min length3

Characters and Unicode

Total characters2104750
Distinct characters59
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4890 ?
Unique (%)2.2%

Sample

1st rowBaltimore
2nd rowDelanco
3rd rowJamaica
4th rowLocust Valley
5th rowJersey City
ValueCountFrequency (%)
chicago 11202
 
3.9%
city 6003
 
2.1%
county 5830
 
2.0%
new 4872
 
1.7%
saint 4017
 
1.4%
baltimore 3837
 
1.3%
washington 3279
 
1.1%
san 3119
 
1.1%
orleans 2985
 
1.0%
philadelphia 2804
 
1.0%
Other values (8304) 242490
83.5%
2023-11-25T22:20:53.223035image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 187969
 
8.9%
o 170698
 
8.1%
e 170005
 
8.1%
n 158457
 
7.5%
i 143263
 
6.8%
l 129545
 
6.2%
t 116502
 
5.5%
r 110036
 
5.2%
s 92556
 
4.4%
65299
 
3.1%
Other values (49) 760420
36.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1730529
82.2%
Uppercase Letter 287133
 
13.6%
Space Separator 65299
 
3.1%
Close Punctuation 10592
 
0.5%
Open Punctuation 10592
 
0.5%
Dash Punctuation 488
 
< 0.1%
Other Punctuation 117
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 187969
10.9%
o 170698
9.9%
e 170005
9.8%
n 158457
9.2%
i 143263
 
8.3%
l 129545
 
7.5%
t 116502
 
6.7%
r 110036
 
6.4%
s 92556
 
5.3%
h 58589
 
3.4%
Other values (17) 392909
22.7%
Uppercase Letter
ValueCountFrequency (%)
C 41864
14.6%
S 25672
 
8.9%
B 25204
 
8.8%
M 20215
 
7.0%
L 18826
 
6.6%
P 18311
 
6.4%
A 14209
 
4.9%
W 13814
 
4.8%
H 13288
 
4.6%
R 11884
 
4.1%
Other values (16) 83846
29.2%
Other Punctuation
ValueCountFrequency (%)
' 70
59.8%
. 47
40.2%
Space Separator
ValueCountFrequency (%)
65299
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10592
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10592
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 488
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2017662
95.9%
Common 87088
 
4.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 187969
 
9.3%
o 170698
 
8.5%
e 170005
 
8.4%
n 158457
 
7.9%
i 143263
 
7.1%
l 129545
 
6.4%
t 116502
 
5.8%
r 110036
 
5.5%
s 92556
 
4.6%
h 58589
 
2.9%
Other values (43) 680042
33.7%
Common
ValueCountFrequency (%)
65299
75.0%
) 10592
 
12.2%
( 10592
 
12.2%
- 488
 
0.6%
' 70
 
0.1%
. 47
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2104746
> 99.9%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 187969
 
8.9%
o 170698
 
8.1%
e 170005
 
8.1%
n 158457
 
7.5%
i 143263
 
6.8%
l 129545
 
6.2%
t 116502
 
5.5%
r 110036
 
5.2%
s 92556
 
4.4%
65299
 
3.1%
Other values (48) 760416
36.1%
None
ValueCountFrequency (%)
ñ 4
100.0%
Distinct186057
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2023-11-25T22:20:53.622532image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length97
Median length73
Mean length21.428495
Min length2

Characters and Unicode

Total characters4827240
Distinct characters92
Distinct categories15 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique173772 ?
Unique (%)77.1%

Sample

1st row600 block of Cokesbury Ave
2nd rowDelaware Ave
3rd rowSutphin Blvd and Rockaway Blvd
4th row99 Horse Hollow Rd
5th rowDwight St
ValueCountFrequency (%)
block 78054
 
8.5%
of 78010
 
8.5%
street 44570
 
4.9%
and 33427
 
3.7%
avenue 30501
 
3.3%
st 30305
 
3.3%
ave 20156
 
2.2%
road 18753
 
2.1%
unknown 15569
 
1.7%
drive 12092
 
1.3%
Other values (38125) 553150
60.5%
2023-11-25T22:20:54.236618image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
694657
 
14.4%
e 368351
 
7.6%
o 329282
 
6.8%
t 266652
 
5.5%
n 242567
 
5.0%
0 220044
 
4.6%
a 215911
 
4.5%
r 211559
 
4.4%
l 186944
 
3.9%
d 126170
 
2.6%
Other values (82) 1965103
40.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2958210
61.3%
Space Separator 694659
 
14.4%
Decimal Number 581967
 
12.1%
Uppercase Letter 571076
 
11.8%
Other Punctuation 18613
 
0.4%
Dash Punctuation 2557
 
0.1%
Final Punctuation 99
 
< 0.1%
Open Punctuation 20
 
< 0.1%
Close Punctuation 19
 
< 0.1%
Other Number 12
 
< 0.1%
Other values (5) 8
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 368351
12.5%
o 329282
11.1%
t 266652
 
9.0%
n 242567
 
8.2%
a 215911
 
7.3%
r 211559
 
7.2%
l 186944
 
6.3%
d 126170
 
4.3%
k 117896
 
4.0%
i 114103
 
3.9%
Other values (18) 778775
26.3%
Uppercase Letter
ValueCountFrequency (%)
S 118321
20.7%
A 64286
11.3%
R 42678
 
7.5%
W 34692
 
6.1%
C 31904
 
5.6%
B 31119
 
5.4%
D 28661
 
5.0%
N 27754
 
4.9%
E 25565
 
4.5%
M 22333
 
3.9%
Other values (16) 143763
25.2%
Decimal Number
ValueCountFrequency (%)
0 220044
37.8%
1 82970
 
14.3%
2 54881
 
9.4%
3 42959
 
7.4%
5 38818
 
6.7%
4 37235
 
6.4%
6 28945
 
5.0%
7 27886
 
4.8%
8 24919
 
4.3%
9 23310
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 17252
92.7%
, 566
 
3.0%
' 292
 
1.6%
/ 268
 
1.4%
# 115
 
0.6%
& 99
 
0.5%
; 14
 
0.1%
" 6
 
< 0.1%
\ 1
 
< 0.1%
Format
ValueCountFrequency (%)
 1
25.0%
1
25.0%
1
25.0%
­ 1
25.0%
Space Separator
ValueCountFrequency (%)
694657
> 99.9%
  2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 2556
> 99.9%
1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 19
95.0%
[ 1
 
5.0%
Close Punctuation
ValueCountFrequency (%)
) 18
94.7%
] 1
 
5.3%
Other Number
ValueCountFrequency (%)
½ 11
91.7%
¼ 1
 
8.3%
Final Punctuation
ValueCountFrequency (%)
99
100.0%
Line Separator
ValueCountFrequency (%)
1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%
Modifier Letter
ValueCountFrequency (%)
ʻ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3529286
73.1%
Common 1297954
 
26.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 368351
 
10.4%
o 329282
 
9.3%
t 266652
 
7.6%
n 242567
 
6.9%
a 215911
 
6.1%
r 211559
 
6.0%
l 186944
 
5.3%
d 126170
 
3.6%
S 118321
 
3.4%
k 117896
 
3.3%
Other values (44) 1345633
38.1%
Common
ValueCountFrequency (%)
694657
53.5%
0 220044
 
17.0%
1 82970
 
6.4%
2 54881
 
4.2%
3 42959
 
3.3%
5 38818
 
3.0%
4 37235
 
2.9%
6 28945
 
2.2%
7 27886
 
2.1%
8 24919
 
1.9%
Other values (28) 44640
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4826992
> 99.9%
None 143
 
< 0.1%
Punctuation 104
 
< 0.1%
Modifier Letters 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
694657
 
14.4%
e 368351
 
7.6%
o 329282
 
6.8%
t 266652
 
5.5%
n 242567
 
5.0%
0 220044
 
4.6%
a 215911
 
4.5%
r 211559
 
4.4%
l 186944
 
3.9%
d 126170
 
2.6%
Other values (68) 1964855
40.7%
None
ValueCountFrequency (%)
ñ 126
88.1%
½ 11
 
7.7%
  2
 
1.4%
 1
 
0.7%
¼ 1
 
0.7%
­ 1
 
0.7%
í 1
 
0.7%
Punctuation
ValueCountFrequency (%)
99
95.2%
1
 
1.0%
1
 
1.0%
1
 
1.0%
1
 
1.0%
1
 
1.0%
Modifier Letters
ValueCountFrequency (%)
ʻ 1
100.0%

n_killed
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
0
179207 
1
46065 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters225272
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 179207
79.6%
1 46065
 
20.4%

Length

2023-11-25T22:20:54.428374image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-25T22:20:54.561602image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
0 179207
79.6%
1 46065
 
20.4%

Most occurring characters

ValueCountFrequency (%)
0 179207
79.6%
1 46065
 
20.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 225272
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 179207
79.6%
1 46065
 
20.4%

Most occurring scripts

ValueCountFrequency (%)
Common 225272
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 179207
79.6%
1 46065
 
20.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 225272
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 179207
79.6%
1 46065
 
20.4%

n_injured
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
0
134261 
1
79926 
2
 
11085

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters225272
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row2
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 134261
59.6%
1 79926
35.5%
2 11085
 
4.9%

Length

2023-11-25T22:20:54.705655image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-25T22:20:54.849148image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
0 134261
59.6%
1 79926
35.5%
2 11085
 
4.9%

Most occurring characters

ValueCountFrequency (%)
0 134261
59.6%
1 79926
35.5%
2 11085
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 225272
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 134261
59.6%
1 79926
35.5%
2 11085
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
Common 225272
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 134261
59.6%
1 79926
35.5%
2 11085
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 225272
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 134261
59.6%
1 79926
35.5%
2 11085
 
4.9%

incident_url
Text

UNIQUE 

Distinct225272
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2023-11-25T22:20:55.265498image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length50
Median length49
Mean length49.06802
Min length48

Characters and Unicode

Total characters11053651
Distinct characters29
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique225272 ?
Unique (%)100.0%

Sample

1st rowhttp://www.gunviolencearchive.org/incident/984353
2nd rowhttp://www.gunviolencearchive.org/incident/1007785
3rd rowhttp://www.gunviolencearchive.org/incident/873575
4th rowhttp://www.gunviolencearchive.org/incident/893251
5th rowhttp://www.gunviolencearchive.org/incident/1023908
ValueCountFrequency (%)
http://www.gunviolencearchive.org/incident/984353 1
 
< 0.1%
http://www.gunviolencearchive.org/incident/964582 1
 
< 0.1%
http://www.gunviolencearchive.org/incident/92218 1
 
< 0.1%
http://www.gunviolencearchive.org/incident/94205 1
 
< 0.1%
http://www.gunviolencearchive.org/incident/873575 1
 
< 0.1%
http://www.gunviolencearchive.org/incident/893251 1
 
< 0.1%
http://www.gunviolencearchive.org/incident/1023908 1
 
< 0.1%
http://www.gunviolencearchive.org/incident/964573 1
 
< 0.1%
http://www.gunviolencearchive.org/incident/1074613 1
 
< 0.1%
http://www.gunviolencearchive.org/incident/958032 1
 
< 0.1%
Other values (225262) 225262
> 99.9%
2023-11-25T22:20:55.912713image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 901088
 
8.2%
/ 901088
 
8.2%
i 901088
 
8.2%
n 901088
 
8.2%
c 675816
 
6.1%
w 675816
 
6.1%
t 675816
 
6.1%
v 450544
 
4.1%
r 450544
 
4.1%
o 450544
 
4.1%
Other values (19) 4070219
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8109792
73.4%
Other Punctuation 1576904
 
14.3%
Decimal Number 1366955
 
12.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 901088
11.1%
i 901088
11.1%
n 901088
11.1%
c 675816
8.3%
w 675816
8.3%
t 675816
8.3%
v 450544
 
5.6%
r 450544
 
5.6%
o 450544
 
5.6%
h 450544
 
5.6%
Other values (6) 1576904
19.4%
Decimal Number
ValueCountFrequency (%)
1 165192
12.1%
3 135590
9.9%
4 134492
9.8%
9 134007
9.8%
2 133731
9.8%
7 133411
9.8%
8 133035
9.7%
5 132970
9.7%
6 132693
9.7%
0 131834
9.6%
Other Punctuation
ValueCountFrequency (%)
/ 901088
57.1%
. 450544
28.6%
: 225272
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 8109792
73.4%
Common 2943859
 
26.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 901088
11.1%
i 901088
11.1%
n 901088
11.1%
c 675816
8.3%
w 675816
8.3%
t 675816
8.3%
v 450544
 
5.6%
r 450544
 
5.6%
o 450544
 
5.6%
h 450544
 
5.6%
Other values (6) 1576904
19.4%
Common
ValueCountFrequency (%)
/ 901088
30.6%
. 450544
15.3%
: 225272
 
7.7%
1 165192
 
5.6%
3 135590
 
4.6%
4 134492
 
4.6%
9 134007
 
4.6%
2 133731
 
4.5%
7 133411
 
4.5%
8 133035
 
4.5%
Other values (3) 397497
13.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11053651
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 901088
 
8.2%
/ 901088
 
8.2%
i 901088
 
8.2%
n 901088
 
8.2%
c 675816
 
6.1%
w 675816
 
6.1%
t 675816
 
6.1%
v 450544
 
4.1%
r 450544
 
4.1%
o 450544
 
4.1%
Other values (19) 4070219
36.8%
Distinct200528
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2023-11-25T22:20:56.251023image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length255
Median length225
Mean length93.707052
Min length2

Characters and Unicode

Total characters21109575
Distinct characters94
Distinct categories15 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique190282 ?
Unique (%)84.5%

Sample

1st rowhttp://abcnews.go.com/US/wireStory/baltimore-gang-member-admits-killing-witness-2013-51040451
2nd rowhttp://www.burlingtoncountytimes.com/news/20171214/man-charged-in-shooting-incident-with-delanco-cop-not-guilty-by-reason-of-insanity
3rd rowhttp://qns.com/story/2017/06/22/second-shooter-convicted-fatally-shooting-jamaica-teenager-riding-bus/
4th rowhttps://patch.com/new-york/glencove/drug-suspect-shot-by-police-idd
5th rowhttp://www.nj.com/hudson/index.ssf/2018/01/murder_trial_of_man_killed_outside_jersey_city_par.html#incart_river_index
ValueCountFrequency (%)
http://blog.tsa.gov 1179
 
0.5%
http://callsforservice.jaxsheriff.org 811
 
0.4%
https://data.oaklandnet.com/public-safety/crimewatch-maps-past-90-days/ym6k-rx7a 492
 
0.2%
unknown 422
 
0.2%
http://itmdapps.ci.mil.wi.us/mpdcalldata/currentcadcalls/callsservice.faces 330
 
0.1%
http://www.springsgov.com/units/police/policeblotter.asp 237
 
0.1%
https://www.facebook.com/pg/policeclips/posts/?ref=page_internal 126
 
0.1%
http://www.tampabay.com/news/hillsborough/crime 107
 
< 0.1%
http://blog.tsa.gov/2016 104
 
< 0.1%
05 104
 
< 0.1%
Other values (200708) 222145
98.3%
2023-11-25T22:20:56.796410image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 1453778
 
6.9%
- 1432528
 
6.8%
e 1398574
 
6.6%
/ 1361558
 
6.4%
o 1223035
 
5.8%
n 1064322
 
5.0%
s 993362
 
4.7%
a 954994
 
4.5%
i 943247
 
4.5%
r 832622
 
3.9%
Other values (84) 9451555
44.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 15124743
71.6%
Other Punctuation 2125974
 
10.1%
Decimal Number 2113689
 
10.0%
Dash Punctuation 1432528
 
6.8%
Uppercase Letter 159680
 
0.8%
Connector Punctuation 128782
 
0.6%
Math Symbol 23181
 
0.1%
Space Separator 859
 
< 0.1%
Open Punctuation 47
 
< 0.1%
Close Punctuation 47
 
< 0.1%
Other values (5) 45
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1453778
 
9.6%
e 1398574
 
9.2%
o 1223035
 
8.1%
n 1064322
 
7.0%
s 993362
 
6.6%
a 954994
 
6.3%
i 943247
 
6.2%
r 832622
 
5.5%
w 822815
 
5.4%
c 795305
 
5.3%
Other values (16) 4642689
30.7%
Uppercase Letter
ValueCountFrequency (%)
S 17938
 
11.2%
P 13526
 
8.5%
C 11507
 
7.2%
N 10566
 
6.6%
D 10081
 
6.3%
M 9485
 
5.9%
W 9053
 
5.7%
A 8672
 
5.4%
E 8132
 
5.1%
F 6243
 
3.9%
Other values (16) 54477
34.1%
Other Punctuation
ValueCountFrequency (%)
/ 1361558
64.0%
. 500857
 
23.6%
: 225923
 
10.6%
# 11484
 
0.5%
? 8828
 
0.4%
& 7606
 
0.4%
% 6390
 
0.3%
, 2859
 
0.1%
! 324
 
< 0.1%
; 117
 
< 0.1%
Other values (5) 28
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 357122
16.9%
0 342336
16.2%
2 305367
14.4%
5 172833
8.2%
3 171107
8.1%
4 166176
7.9%
6 161314
7.6%
7 158405
7.5%
8 140781
 
6.7%
9 138248
 
6.5%
Math Symbol
ValueCountFrequency (%)
= 16244
70.1%
+ 6899
29.8%
~ 23
 
0.1%
| 15
 
0.1%
Open Punctuation
ValueCountFrequency (%)
[ 37
78.7%
( 10
 
21.3%
Close Punctuation
ValueCountFrequency (%)
] 37
78.7%
) 10
 
21.3%
Modifier Symbol
ValueCountFrequency (%)
^ 9
69.2%
` 4
30.8%
Dash Punctuation
ValueCountFrequency (%)
- 1432528
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 128782
100.0%
Space Separator
ValueCountFrequency (%)
859
100.0%
Final Punctuation
ValueCountFrequency (%)
16
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 9
100.0%
Control
ValueCountFrequency (%)
6
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15284423
72.4%
Common 5825152
 
27.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1453778
 
9.5%
e 1398574
 
9.2%
o 1223035
 
8.0%
n 1064322
 
7.0%
s 993362
 
6.5%
a 954994
 
6.2%
i 943247
 
6.2%
r 832622
 
5.4%
w 822815
 
5.4%
c 795305
 
5.2%
Other values (42) 4802369
31.4%
Common
ValueCountFrequency (%)
- 1432528
24.6%
/ 1361558
23.4%
. 500857
 
8.6%
1 357122
 
6.1%
0 342336
 
5.9%
2 305367
 
5.2%
: 225923
 
3.9%
5 172833
 
3.0%
3 171107
 
2.9%
4 166176
 
2.9%
Other values (32) 789345
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21109556
> 99.9%
Punctuation 19
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1453778
 
6.9%
- 1432528
 
6.8%
e 1398574
 
6.6%
/ 1361558
 
6.4%
o 1223035
 
5.8%
n 1064322
 
5.0%
s 993362
 
4.7%
a 954994
 
4.5%
i 943247
 
4.5%
r 832622
 
3.9%
Other values (81) 9451536
44.8%
Punctuation
ValueCountFrequency (%)
16
84.2%
2
 
10.5%
1
 
5.3%

incident_url_fields_missing
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
False
225272 
ValueCountFrequency (%)
False 225272
100.0%
2023-11-25T22:20:56.939306image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

congressional_district
Real number (ℝ)

Distinct54
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.9004981
Minimum0
Maximum53
Zeros400
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size3.4 MiB
2023-11-25T22:20:57.098780image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median5
Q310
95-th percentile26
Maximum53
Range53
Interquartile range (IQR)8

Descriptive statistics

Standard deviation8.3170894
Coefficient of variation (CV)1.0527298
Kurtosis5.3561352
Mean7.9004981
Median Absolute Deviation (MAD)3
Skewness2.1225116
Sum1779761
Variance69.173976
MonotonicityNot monotonic
2023-11-25T22:20:57.319873image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 36534
16.2%
2 27178
12.1%
7 20699
 
9.2%
3 20052
 
8.9%
4 17776
 
7.9%
5 16713
 
7.4%
9 9669
 
4.3%
6 8992
 
4.0%
8 6884
 
3.1%
13 6684
 
3.0%
Other values (44) 54091
24.0%
ValueCountFrequency (%)
0 400
 
0.2%
1 36534
16.2%
2 27178
12.1%
3 20052
8.9%
4 17776
7.9%
5 16713
7.4%
6 8992
 
4.0%
7 20699
9.2%
8 6884
 
3.1%
9 9669
 
4.3%
ValueCountFrequency (%)
53 122
 
0.1%
52 147
 
0.1%
51 208
0.1%
50 107
 
< 0.1%
49 91
 
< 0.1%
48 111
 
< 0.1%
47 272
0.1%
46 239
0.1%
45 34
 
< 0.1%
44 371
0.2%
Distinct148
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2023-11-25T22:20:57.515433image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length148
Median length10
Mean length11.08705
Min length8

Characters and Unicode

Total characters2497602
Distinct characters24
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)< 0.1%

Sample

1st row0::Unknown
2nd row0::Unknown
3rd row0::Unknown
4th row0::Unknown
5th row0::Unknown
ValueCountFrequency (%)
0::unknown 208247
92.4%
0::unknown||1::unknown 5659
 
2.5%
0::stolen 4453
 
2.0%
0::unknown||1::unknown||2::unknown 1368
 
0.6%
0::not-stolen 1245
 
0.6%
0::stolen||1::stolen 707
 
0.3%
0::unknown||1::unknown||2::unknown||3::unknown 537
 
0.2%
0::stolen||1::unknown 368
 
0.2%
0:unknown 307
 
0.1%
0::stolen||1::stolen||2::stolen 293
 
0.1%
Other values (138) 2088
 
0.9%
2023-11-25T22:20:57.952500image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 713361
28.6%
: 492134
19.7%
o 247806
 
9.9%
U 233563
 
9.4%
k 233563
 
9.4%
w 233563
 
9.4%
0 225337
 
9.0%
| 41911
 
1.7%
t 14243
 
0.6%
l 12672
 
0.5%
Other values (14) 49449
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1469451
58.8%
Other Punctuation 492134
 
19.7%
Decimal Number 246300
 
9.9%
Uppercase Letter 246235
 
9.9%
Math Symbol 41911
 
1.7%
Dash Punctuation 1571
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 225337
91.5%
1 11082
 
4.5%
2 4038
 
1.6%
3 2143
 
0.9%
4 1324
 
0.5%
5 903
 
0.4%
6 630
 
0.3%
7 404
 
0.2%
8 274
 
0.1%
9 165
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
n 713361
48.5%
o 247806
 
16.9%
k 233563
 
15.9%
w 233563
 
15.9%
t 14243
 
1.0%
l 12672
 
0.9%
e 12672
 
0.9%
s 1571
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
U 233563
94.9%
S 11101
 
4.5%
N 1571
 
0.6%
Other Punctuation
ValueCountFrequency (%)
: 492134
100.0%
Math Symbol
ValueCountFrequency (%)
| 41911
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1571
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1715686
68.7%
Common 781916
31.3%

Most frequent character per script

Common
ValueCountFrequency (%)
: 492134
62.9%
0 225337
28.8%
| 41911
 
5.4%
1 11082
 
1.4%
2 4038
 
0.5%
3 2143
 
0.3%
- 1571
 
0.2%
4 1324
 
0.2%
5 903
 
0.1%
6 630
 
0.1%
Other values (3) 843
 
0.1%
Latin
ValueCountFrequency (%)
n 713361
41.6%
o 247806
 
14.4%
U 233563
 
13.6%
k 233563
 
13.6%
w 233563
 
13.6%
t 14243
 
0.8%
l 12672
 
0.7%
e 12672
 
0.7%
S 11101
 
0.6%
N 1571
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2497602
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 713361
28.6%
: 492134
19.7%
o 247806
 
9.9%
U 233563
 
9.4%
k 233563
 
9.4%
w 233563
 
9.4%
0 225337
 
9.0%
| 41911
 
1.7%
t 14243
 
0.6%
l 12672
 
0.5%
Other values (14) 49449
 
2.0%
Distinct1969
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2023-11-25T22:20:58.203993image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length219
Median length10
Mean length10.988494
Min length5

Characters and Unicode

Total characters2475400
Distinct characters44
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1414 ?
Unique (%)0.6%

Sample

1st row0::Unknown
2nd row0::Unknown
3rd row0::Unknown
4th row0::Unknown
5th row0::Unknown
ValueCountFrequency (%)
0::unknown 181963
74.6%
0::handgun 12357
 
5.1%
auto 4607
 
1.9%
0::9mm 4438
 
1.8%
0::22 2457
 
1.0%
lr 2429
 
1.0%
0::unknown||1::unknown 2223
 
0.9%
0::40 2165
 
0.9%
sw 2139
 
0.9%
0::380 2015
 
0.8%
Other values (1883) 27168
 
11.1%
2023-11-25T22:20:58.681359image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 626296
25.3%
: 492143
19.9%
0 230937
 
9.3%
o 202907
 
8.2%
U 193787
 
7.8%
k 193787
 
7.8%
w 193787
 
7.8%
| 41921
 
1.7%
u 30975
 
1.3%
g 27687
 
1.1%
Other values (34) 241173
 
9.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1370444
55.4%
Other Punctuation 492938
 
19.9%
Decimal Number 297021
 
12.0%
Uppercase Letter 247942
 
10.0%
Math Symbol 41921
 
1.7%
Space Separator 18689
 
0.8%
Dash Punctuation 2253
 
0.1%
Open Punctuation 2096
 
0.1%
Close Punctuation 2096
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 626296
45.7%
o 202907
 
14.8%
k 193787
 
14.1%
w 193787
 
14.1%
u 30975
 
2.3%
g 27687
 
2.0%
a 22789
 
1.7%
d 20572
 
1.5%
m 13439
 
1.0%
t 10088
 
0.7%
Other values (7) 28117
 
2.1%
Decimal Number
ValueCountFrequency (%)
0 230937
77.8%
2 15832
 
5.3%
1 13525
 
4.6%
3 8939
 
3.0%
4 7311
 
2.5%
9 6185
 
2.1%
5 5717
 
1.9%
8 4302
 
1.4%
7 2746
 
0.9%
6 1527
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
U 193787
78.2%
H 20572
 
8.3%
R 9538
 
3.8%
S 7914
 
3.2%
A 7601
 
3.1%
L 3095
 
1.2%
W 2738
 
1.1%
O 968
 
0.4%
M 934
 
0.4%
K 795
 
0.3%
Other Punctuation
ValueCountFrequency (%)
: 492143
99.8%
. 795
 
0.2%
Math Symbol
ValueCountFrequency (%)
| 41921
100.0%
Space Separator
ValueCountFrequency (%)
18689
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2253
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 2096
100.0%
Close Punctuation
ValueCountFrequency (%)
] 2096
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1618386
65.4%
Common 857014
34.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 626296
38.7%
o 202907
 
12.5%
U 193787
 
12.0%
k 193787
 
12.0%
w 193787
 
12.0%
u 30975
 
1.9%
g 27687
 
1.7%
a 22789
 
1.4%
d 20572
 
1.3%
H 20572
 
1.3%
Other values (17) 85227
 
5.3%
Common
ValueCountFrequency (%)
: 492143
57.4%
0 230937
26.9%
| 41921
 
4.9%
18689
 
2.2%
2 15832
 
1.8%
1 13525
 
1.6%
3 8939
 
1.0%
4 7311
 
0.9%
9 6185
 
0.7%
5 5717
 
0.7%
Other values (7) 15815
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2475400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 626296
25.3%
: 492143
19.9%
0 230937
 
9.3%
o 202907
 
8.2%
U 193787
 
7.8%
k 193787
 
7.8%
w 193787
 
7.8%
| 41921
 
1.7%
u 30975
 
1.3%
g 27687
 
1.1%
Other values (34) 241173
 
9.7%
Distinct16513
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2023-11-25T22:20:58.954910image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length662
Median length570
Mean length80.457411
Min length8

Characters and Unicode

Total characters18124802
Distinct characters64
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10990 ?
Unique (%)4.9%

Sample

1st rowShot - Dead (murder, accidental, suicide)||Gang involvement||Drug involvement
2nd rowShot - Wounded/Injured||Officer Involved Incident||Officer Involved Shooting - Officer shot||Officer Involved Shooting - subject/suspect/perpetrator shot
3rd rowShot - Dead (murder, accidental, suicide)||Gang involvement||Possession of gun by felon or prohibited person
4th rowShot - Wounded/Injured||Officer Involved Incident||Officer Involved Shooting - subject/suspect/perpetrator shot||Drug involvement
5th rowShot - Dead (murder, accidental, suicide)||House party
ValueCountFrequency (%)
225944
 
11.3%
shot 129063
 
6.4%
of 70084
 
3.5%
no 57834
 
2.9%
wounded/injured 46423
 
2.3%
accidental 46148
 
2.3%
dead 45707
 
2.3%
murder 45707
 
2.3%
shots 42352
 
2.1%
fired 41832
 
2.1%
Other values (2568) 1252449
62.5%
2023-11-25T22:20:59.479903image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1778271
 
9.8%
e 1441446
 
8.0%
o 1385675
 
7.6%
n 1371929
 
7.6%
i 1102508
 
6.1%
d 969438
 
5.3%
r 969425
 
5.3%
t 883745
 
4.9%
s 834852
 
4.6%
u 671127
 
3.7%
Other values (54) 6716386
37.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13214661
72.9%
Space Separator 1778271
 
9.8%
Uppercase Letter 1445097
 
8.0%
Math Symbol 617788
 
3.4%
Other Punctuation 475410
 
2.6%
Dash Punctuation 296714
 
1.6%
Open Punctuation 143352
 
0.8%
Close Punctuation 143352
 
0.8%
Decimal Number 7467
 
< 0.1%
Modifier Symbol 2690
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1441446
10.9%
o 1385675
10.5%
n 1371929
10.4%
i 1102508
 
8.3%
d 969438
 
7.3%
r 969425
 
7.3%
t 883745
 
6.7%
s 834852
 
6.3%
u 671127
 
5.1%
c 593048
 
4.5%
Other values (15) 2991468
22.6%
Uppercase Letter
ValueCountFrequency (%)
I 280895
19.4%
S 275661
19.1%
D 128039
8.9%
N 102754
 
7.1%
A 97777
 
6.8%
W 95752
 
6.6%
P 57374
 
4.0%
F 52368
 
3.6%
G 46982
 
3.3%
O 46724
 
3.2%
Other values (12) 260771
18.0%
Decimal Number
ValueCountFrequency (%)
1 1789
24.0%
5 1789
24.0%
4 1789
24.0%
7 1789
24.0%
0 311
 
4.2%
Other Punctuation
ValueCountFrequency (%)
/ 352516
74.1%
, 120295
 
25.3%
: 2000
 
0.4%
& 599
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 136167
95.0%
{ 7185
 
5.0%
Close Punctuation
ValueCountFrequency (%)
) 136167
95.0%
} 7185
 
5.0%
Space Separator
ValueCountFrequency (%)
1778271
100.0%
Math Symbol
ValueCountFrequency (%)
| 617788
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 296714
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 2690
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14659758
80.9%
Common 3465044
 
19.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1441446
 
9.8%
o 1385675
 
9.5%
n 1371929
 
9.4%
i 1102508
 
7.5%
d 969438
 
6.6%
r 969425
 
6.6%
t 883745
 
6.0%
s 834852
 
5.7%
u 671127
 
4.6%
c 593048
 
4.0%
Other values (37) 4436565
30.3%
Common
ValueCountFrequency (%)
1778271
51.3%
| 617788
 
17.8%
/ 352516
 
10.2%
- 296714
 
8.6%
( 136167
 
3.9%
) 136167
 
3.9%
, 120295
 
3.5%
} 7185
 
0.2%
{ 7185
 
0.2%
^ 2690
 
0.1%
Other values (7) 10066
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18124802
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1778271
 
9.8%
e 1441446
 
8.0%
o 1385675
 
7.6%
n 1371929
 
7.6%
i 1102508
 
6.1%
d 969438
 
5.3%
r 969425
 
5.3%
t 883745
 
4.9%
s 834852
 
4.6%
u 671127
 
3.7%
Other values (54) 6716386
37.1%

latitude
Real number (ℝ)

Distinct97239
Distinct (%)43.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.589948
Minimum19.1114
Maximum71.3368
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 MiB
2023-11-25T22:20:59.697885image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum19.1114
5-th percentile29.346375
Q133.9318
median38.62065
Q341.4643
95-th percentile44.051
Maximum71.3368
Range52.2254
Interquartile range (IQR)7.5325

Descriptive statistics

Standard deviation5.1202
Coefficient of variation (CV)0.13621195
Kurtosis1.9236426
Mean37.589948
Median Absolute Deviation (MAD)3.31785
Skewness0.2096473
Sum8467962.7
Variance26.216448
MonotonicityNot monotonic
2023-11-25T22:21:00.113212image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41.47307945 660
 
0.3%
30.84048662 505
 
0.2%
28.23180486 365
 
0.2%
40.49097997 364
 
0.2%
40.32786907 332
 
0.1%
30.52723681 329
 
0.1%
42.68984191 327
 
0.1%
36.11558537 287
 
0.1%
35.47406981 258
 
0.1%
40.27667384 256
 
0.1%
Other values (97229) 221589
98.4%
ValueCountFrequency (%)
19.1114 1
< 0.1%
19.2 1
< 0.1%
19.2017 1
< 0.1%
19.4243 1
< 0.1%
19.4331 1
< 0.1%
19.4475 1
< 0.1%
19.4554 1
< 0.1%
19.4578 1
< 0.1%
19.4756 1
< 0.1%
19.4969 1
< 0.1%
ValueCountFrequency (%)
71.3368 1
< 0.1%
71.3005 1
< 0.1%
71.3001 1
< 0.1%
71.3 1
< 0.1%
71.2997 1
< 0.1%
71.2921 1
< 0.1%
71.2906 1
< 0.1%
70.6698 1
< 0.1%
70.1981 1
< 0.1%
67.5533 1
< 0.1%
Distinct25375
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2023-11-25T22:21:00.529438image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length100
Median length7
Mean length8.7767055
Min length1

Characters and Unicode

Total characters1977146
Distinct characters92
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21915 ?
Unique (%)9.7%

Sample

1st rowUnknown
2nd rowUnknown
3rd rowUnknown
4th rowUnknown
5th rowUnknown
ValueCountFrequency (%)
unknown 186278
64.8%
apartments 3979
 
1.4%
park 3114
 
1.1%
school 1796
 
0.6%
neighborhood 1313
 
0.5%
high 1168
 
0.4%
airport 1061
 
0.4%
inn 964
 
0.3%
and 800
 
0.3%
station 764
 
0.3%
Other values (13837) 86028
29.9%
2023-11-25T22:21:01.215868image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 599487
30.3%
o 230915
 
11.7%
k 194707
 
9.8%
w 191131
 
9.7%
U 187247
 
9.5%
61999
 
3.1%
e 55379
 
2.8%
a 50185
 
2.5%
r 44693
 
2.3%
t 41203
 
2.1%
Other values (82) 320200
16.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1616192
81.7%
Uppercase Letter 288865
 
14.6%
Space Separator 62009
 
3.1%
Other Punctuation 4150
 
0.2%
Decimal Number 2454
 
0.1%
Open Punctuation 988
 
< 0.1%
Close Punctuation 986
 
< 0.1%
Dash Punctuation 969
 
< 0.1%
Final Punctuation 512
 
< 0.1%
Initial Punctuation 8
 
< 0.1%
Other values (3) 13
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 599487
37.1%
o 230915
 
14.3%
k 194707
 
12.0%
w 191131
 
11.8%
e 55379
 
3.4%
a 50185
 
3.1%
r 44693
 
2.8%
t 41203
 
2.5%
i 33026
 
2.0%
l 31053
 
1.9%
Other values (20) 144413
 
8.9%
Uppercase Letter
ValueCountFrequency (%)
U 187247
64.8%
S 11013
 
3.8%
C 10019
 
3.5%
A 9412
 
3.3%
P 8092
 
2.8%
M 7127
 
2.5%
H 6182
 
2.1%
B 5535
 
1.9%
L 4490
 
1.6%
T 4375
 
1.5%
Other values (16) 35373
 
12.2%
Other Punctuation
ValueCountFrequency (%)
' 2478
59.7%
& 666
 
16.0%
. 492
 
11.9%
/ 340
 
8.2%
, 123
 
3.0%
" 30
 
0.7%
# 15
 
0.4%
@ 3
 
0.1%
! 2
 
< 0.1%
; 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 422
17.2%
7 396
16.1%
6 351
14.3%
2 261
10.6%
0 235
9.6%
8 174
7.1%
3 160
 
6.5%
5 160
 
6.5%
4 157
 
6.4%
9 138
 
5.6%
Space Separator
ValueCountFrequency (%)
61999
> 99.9%
8
 
< 0.1%
  2
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 985
99.7%
[ 3
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 983
99.7%
] 3
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 964
99.5%
5
 
0.5%
Final Punctuation
ValueCountFrequency (%)
511
99.8%
1
 
0.2%
Initial Punctuation
ValueCountFrequency (%)
7
87.5%
1
 
12.5%
Modifier Symbol
ValueCountFrequency (%)
` 5
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1905057
96.4%
Common 72089
 
3.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 599487
31.5%
o 230915
 
12.1%
k 194707
 
10.2%
w 191131
 
10.0%
U 187247
 
9.8%
e 55379
 
2.9%
a 50185
 
2.6%
r 44693
 
2.3%
t 41203
 
2.2%
i 33026
 
1.7%
Other values (46) 277084
14.5%
Common
ValueCountFrequency (%)
61999
86.0%
' 2478
 
3.4%
( 985
 
1.4%
) 983
 
1.4%
- 964
 
1.3%
& 666
 
0.9%
511
 
0.7%
. 492
 
0.7%
1 422
 
0.6%
7 396
 
0.5%
Other values (26) 2193
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1976595
> 99.9%
Punctuation 533
 
< 0.1%
None 18
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 599487
30.3%
o 230915
 
11.7%
k 194707
 
9.9%
w 191131
 
9.7%
U 187247
 
9.5%
61999
 
3.1%
e 55379
 
2.8%
a 50185
 
2.5%
r 44693
 
2.3%
t 41203
 
2.1%
Other values (71) 319649
16.2%
Punctuation
ValueCountFrequency (%)
511
95.9%
8
 
1.5%
7
 
1.3%
5
 
0.9%
1
 
0.2%
1
 
0.2%
None
ValueCountFrequency (%)
é 11
61.1%
  2
 
11.1%
ñ 2
 
11.1%
à 2
 
11.1%
ó 1
 
5.6%

longitude
Real number (ℝ)

Distinct107549
Distinct (%)47.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-89.233485
Minimum-171.429
Maximum97.4331
Zeros0
Zeros (%)0.0%
Negative225267
Negative (%)> 99.9%
Memory size3.4 MiB
2023-11-25T22:21:01.442550image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum-171.429
5-th percentile-121.32445
Q1-93.799
median-86.24045
Q3-79.9931
95-th percentile-73.197755
Maximum97.4331
Range268.8621
Interquartile range (IQR)13.8059

Descriptive statistics

Standard deviation14.30432
Coefficient of variation (CV)-0.16030216
Kurtosis2.6381362
Mean-89.233485
Median Absolute Deviation (MAD)6.8324484
Skewness-1.3681677
Sum-20101806
Variance204.61358
MonotonicityNot monotonic
2023-11-25T22:21:01.657430image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-88.10175084 660
 
0.3%
-97.26530572 505
 
0.2%
-81.68843331 365
 
0.2%
-82.90022196 364
 
0.2%
-76.82202365 332
 
0.1%
-91.10226277 329
 
0.1%
-83.97847523 327
 
0.1%
-119.9246907 287
 
0.1%
-79.40800158 258
 
0.1%
-86.30992648 256
 
0.1%
Other values (107539) 221589
98.4%
ValueCountFrequency (%)
-171.429 1
< 0.1%
-166.541 1
< 0.1%
-166.097 1
< 0.1%
-165.711 2
< 0.1%
-165.586 1
< 0.1%
-165.509 1
< 0.1%
-165.444 1
< 0.1%
-164.76 1
< 0.1%
-164.621 1
< 0.1%
-164.62 1
< 0.1%
ValueCountFrequency (%)
97.4331 2
< 0.1%
96.7591 1
< 0.1%
90.37 1
< 0.1%
80.9491 1
< 0.1%
-67.2711 1
< 0.1%
-67.275 1
< 0.1%
-67.2996 1
< 0.1%
-67.3318 1
< 0.1%
-67.4012 1
< 0.1%
-67.7617 1
< 0.1%

n_guns_involved
Real number (ℝ)

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0930786
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 MiB
2023-11-25T22:21:01.830972image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum11
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.55602775
Coefficient of variation (CV)0.50868049
Kurtosis117.6482
Mean1.0930786
Median Absolute Deviation (MAD)0
Skewness9.6302415
Sum246240
Variance0.30916686
MonotonicityNot monotonic
2023-11-25T22:21:01.984923image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 214254
95.1%
2 6979
 
3.1%
3 1895
 
0.8%
4 819
 
0.4%
5 421
 
0.2%
6 274
 
0.1%
7 226
 
0.1%
8 130
 
0.1%
9 109
 
< 0.1%
10 100
 
< 0.1%
ValueCountFrequency (%)
1 214254
95.1%
2 6979
 
3.1%
3 1895
 
0.8%
4 819
 
0.4%
5 421
 
0.2%
6 274
 
0.1%
7 226
 
0.1%
8 130
 
0.1%
9 109
 
< 0.1%
10 100
 
< 0.1%
ValueCountFrequency (%)
11 65
 
< 0.1%
10 100
 
< 0.1%
9 109
 
< 0.1%
8 130
 
0.1%
7 226
 
0.1%
6 274
 
0.1%
5 421
 
0.2%
4 819
 
0.4%
3 1895
 
0.8%
2 6979
3.1%

notes
Text

Distinct127262
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2023-11-25T22:21:02.356928image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length256
Median length237
Mean length39.258416
Min length1

Characters and Unicode

Total characters8843822
Distinct characters110
Distinct categories18 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique123356 ?
Unique (%)54.8%

Sample

1st rowBlack Guerilla Family gang
2nd rowscuffle during arrest led to suspect being shot 4 times and officer being shot once with his own gun
3rd rowGirl shot dead while riding MTA Q6 Bus; vic was unintended target of gang related shooting; 40.673074, -73.787983 ;
4th rowTraffic stop; backed car into approaching officer, knocked him to ground
5th rowNo Notes
ValueCountFrequency (%)
no 85239
 
5.6%
notes 76780
 
5.0%
shot 47443
 
3.1%
in 43392
 
2.8%
man 24117
 
1.6%
at 23241
 
1.5%
and 22398
 
1.5%
of 16962
 
1.1%
fired 16716
 
1.1%
to 16486
 
1.1%
Other values (56282) 1151325
75.5%
2023-11-25T22:21:02.994068image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1294454
14.6%
e 721073
 
8.2%
o 653857
 
7.4%
t 567749
 
6.4%
n 488639
 
5.5%
s 481646
 
5.4%
a 453319
 
5.1%
i 440500
 
5.0%
r 425336
 
4.8%
d 292924
 
3.3%
Other values (100) 3024325
34.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6483107
73.3%
Space Separator 1294458
 
14.6%
Uppercase Letter 402129
 
4.5%
Decimal Number 302827
 
3.4%
Other Punctuation 291670
 
3.3%
Control 33744
 
0.4%
Dash Punctuation 31998
 
0.4%
Close Punctuation 1280
 
< 0.1%
Open Punctuation 1278
 
< 0.1%
Final Punctuation 649
 
< 0.1%
Other values (8) 682
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 721073
11.1%
o 653857
 
10.1%
t 567749
 
8.8%
n 488639
 
7.5%
s 481646
 
7.4%
a 453319
 
7.0%
i 440500
 
6.8%
r 425336
 
6.6%
d 292924
 
4.5%
h 266180
 
4.1%
Other values (18) 1691884
26.1%
Uppercase Letter
ValueCountFrequency (%)
N 160690
40.0%
S 28303
 
7.0%
M 24345
 
6.1%
A 20605
 
5.1%
C 19672
 
4.9%
P 17145
 
4.3%
D 12618
 
3.1%
B 12129
 
3.0%
T 11142
 
2.8%
R 10851
 
2.7%
Other values (17) 84629
21.0%
Other Punctuation
ValueCountFrequency (%)
, 126442
43.4%
. 74338
25.5%
; 57492
19.7%
/ 14344
 
4.9%
: 7220
 
2.5%
' 6964
 
2.4%
& 2226
 
0.8%
" 1427
 
0.5%
# 569
 
0.2%
* 345
 
0.1%
Other values (5) 303
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 49590
16.4%
2 41881
13.8%
0 33410
11.0%
3 32810
10.8%
4 27892
9.2%
8 24871
8.2%
5 24604
8.1%
9 24411
8.1%
7 23111
7.6%
6 20247
6.7%
Math Symbol
ValueCountFrequency (%)
~ 205
67.9%
+ 58
 
19.2%
= 35
 
11.6%
| 2
 
0.7%
< 1
 
0.3%
> 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1294454
> 99.9%
  2
 
< 0.1%
2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 31985
> 99.9%
11
 
< 0.1%
2
 
< 0.1%
Control
ValueCountFrequency (%)
26808
79.4%
6933
 
20.5%
3
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 979
76.5%
] 301
 
23.5%
Open Punctuation
ValueCountFrequency (%)
( 977
76.4%
[ 301
 
23.6%
Final Punctuation
ValueCountFrequency (%)
582
89.7%
67
 
10.3%
Initial Punctuation
ValueCountFrequency (%)
72
82.8%
15
 
17.2%
Format
ValueCountFrequency (%)
1
50.0%
1
50.0%
Currency Symbol
ValueCountFrequency (%)
$ 234
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 47
100.0%
Other Symbol
ValueCountFrequency (%)
° 7
100.0%
Other Number
ValueCountFrequency (%)
½ 2
100.0%
Modifier Letter
ValueCountFrequency (%)
ʻ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6885236
77.9%
Common 1958586
 
22.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1294454
66.1%
, 126442
 
6.5%
. 74338
 
3.8%
; 57492
 
2.9%
1 49590
 
2.5%
2 41881
 
2.1%
0 33410
 
1.7%
3 32810
 
1.7%
- 31985
 
1.6%
4 27892
 
1.4%
Other values (45) 188292
 
9.6%
Latin
ValueCountFrequency (%)
e 721073
 
10.5%
o 653857
 
9.5%
t 567749
 
8.2%
n 488639
 
7.1%
s 481646
 
7.0%
a 453319
 
6.6%
i 440500
 
6.4%
r 425336
 
6.2%
d 292924
 
4.3%
h 266180
 
3.9%
Other values (45) 2094013
30.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8843039
> 99.9%
Punctuation 753
 
< 0.1%
None 29
 
< 0.1%
Modifier Letters 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1294454
14.6%
e 721073
 
8.2%
o 653857
 
7.4%
t 567749
 
6.4%
n 488639
 
5.5%
s 481646
 
5.4%
a 453319
 
5.1%
i 440500
 
5.0%
r 425336
 
4.8%
d 292924
 
3.3%
Other values (84) 3023542
34.2%
Punctuation
ValueCountFrequency (%)
582
77.3%
72
 
9.6%
67
 
8.9%
15
 
2.0%
11
 
1.5%
2
 
0.3%
2
 
0.3%
1
 
0.1%
1
 
0.1%
None
ValueCountFrequency (%)
é 11
37.9%
° 7
24.1%
ñ 6
20.7%
  2
 
6.9%
½ 2
 
6.9%
Ñ 1
 
3.4%
Modifier Letters
ValueCountFrequency (%)
ʻ 1
100.0%
Distinct13517
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2023-11-25T22:21:03.302550image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length212
Median length5
Mean length6.7582256
Min length3

Characters and Unicode

Total characters1522439
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9486 ?
Unique (%)4.2%

Sample

1st row0::22||1::25
2nd row1::22
3rd row0::14||1::15||2::21
4th row0::22
5th row0::21||1::19
ValueCountFrequency (%)
0::29 92803
41.2%
0::24 3794
 
1.7%
0::23 3723
 
1.7%
0::22 3714
 
1.6%
0::19 3692
 
1.6%
0::21 3598
 
1.6%
0::18 3518
 
1.6%
0::20 3510
 
1.6%
0::25 3482
 
1.5%
0::26 3266
 
1.4%
Other values (13507) 100172
44.5%
2023-11-25T22:21:03.854603image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 562578
37.0%
0 231370
15.2%
2 203833
 
13.4%
| 113906
 
7.5%
9 111399
 
7.3%
1 108643
 
7.1%
3 61961
 
4.1%
4 37308
 
2.5%
5 28830
 
1.9%
8 21798
 
1.4%
Other values (2) 40813
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 845955
55.6%
Other Punctuation 562578
37.0%
Math Symbol 113906
 
7.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 231370
27.4%
2 203833
24.1%
9 111399
13.2%
1 108643
12.8%
3 61961
 
7.3%
4 37308
 
4.4%
5 28830
 
3.4%
8 21798
 
2.6%
6 20492
 
2.4%
7 20321
 
2.4%
Other Punctuation
ValueCountFrequency (%)
: 562578
100.0%
Math Symbol
ValueCountFrequency (%)
| 113906
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1522439
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 562578
37.0%
0 231370
15.2%
2 203833
 
13.4%
| 113906
 
7.5%
9 111399
 
7.3%
1 108643
 
7.1%
3 61961
 
4.1%
4 37308
 
2.5%
5 28830
 
1.9%
8 21798
 
1.4%
Other values (2) 40813
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1522439
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 562578
37.0%
0 231370
15.2%
2 203833
 
13.4%
| 113906
 
7.5%
9 111399
 
7.3%
1 108643
 
7.1%
3 61961
 
4.1%
4 37308
 
2.5%
5 28830
 
1.9%
8 21798
 
1.4%
Other values (2) 40813
 
2.7%
Distinct668
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2023-11-25T22:21:04.184664image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length423
Median length12
Mean length19.209826
Min length11

Characters and Unicode

Total characters4327436
Distinct characters26
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique333 ?
Unique (%)0.1%

Sample

1st row0::Adult 18+||1::Adult 18+
2nd row1::Adult 18+
3rd row0::Teen 12-17||1::Teen 12-17||2::Adult 18+
4th row0::Adult 18+
5th row0::Adult 18+||1::Adult 18+
ValueCountFrequency (%)
18 209573
37.1%
0::adult 201453
35.6%
18+||1::adult 63553
 
11.2%
18+||2::adult 20305
 
3.6%
12-17 14023
 
2.5%
0::teen 12581
 
2.2%
18+||3::adult 7164
 
1.3%
1::adult 5203
 
0.9%
18+||1::teen 3082
 
0.5%
0:adult 2698
 
0.5%
Other values (168) 25579
 
4.5%
2023-11-25T22:21:04.740571image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 674175
15.6%
1 447720
10.3%
339942
7.9%
d 316708
7.3%
l 316708
7.3%
8 313050
7.2%
A 312919
7.2%
u 312919
7.2%
t 312919
7.2%
+ 312919
7.2%
Other values (16) 667457
15.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1336534
30.9%
Decimal Number 1070308
24.7%
Other Punctuation 674175
15.6%
Math Symbol 539512
12.5%
Space Separator 339942
 
7.9%
Uppercase Letter 339942
 
7.9%
Dash Punctuation 27023
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 447720
41.8%
8 313050
29.2%
0 223027
20.8%
2 48625
 
4.5%
7 23488
 
2.2%
3 9244
 
0.9%
4 3328
 
0.3%
5 1234
 
0.1%
6 510
 
< 0.1%
9 82
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
d 316708
23.7%
l 316708
23.7%
u 312919
23.4%
t 312919
23.4%
e 46468
 
3.5%
n 23234
 
1.7%
h 3789
 
0.3%
i 3789
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
A 312919
92.1%
T 23234
 
6.8%
C 3789
 
1.1%
Math Symbol
ValueCountFrequency (%)
+ 312919
58.0%
| 226593
42.0%
Other Punctuation
ValueCountFrequency (%)
: 674175
100.0%
Space Separator
ValueCountFrequency (%)
339942
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27023
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2650960
61.3%
Latin 1676476
38.7%

Most frequent character per script

Common
ValueCountFrequency (%)
: 674175
25.4%
1 447720
16.9%
339942
12.8%
8 313050
11.8%
+ 312919
11.8%
| 226593
 
8.5%
0 223027
 
8.4%
2 48625
 
1.8%
- 27023
 
1.0%
7 23488
 
0.9%
Other values (5) 14398
 
0.5%
Latin
ValueCountFrequency (%)
d 316708
18.9%
l 316708
18.9%
A 312919
18.7%
u 312919
18.7%
t 312919
18.7%
e 46468
 
2.8%
T 23234
 
1.4%
n 23234
 
1.4%
C 3789
 
0.2%
h 3789
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4327436
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 674175
15.6%
1 447720
10.3%
339942
7.9%
d 316708
7.3%
l 316708
7.3%
8 313050
7.2%
A 312919
7.2%
u 312919
7.2%
t 312919
7.2%
+ 312919
7.2%
Other values (16) 667457
15.4%
Distinct623
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2023-11-25T22:21:04.966495image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length285
Median length7
Mean length12.267539
Min length6

Characters and Unicode

Total characters2763533
Distinct characters21
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique344 ?
Unique (%)0.2%

Sample

1st row0::Male||1::Male
2nd row0::Male||1::Male
3rd row0::Female||1::Male||2::Male
4th row0::Male
5th row0::Male||1::Male
ValueCountFrequency (%)
0::male 127216
56.5%
0::male||1::male 41335
 
18.3%
0::male||1::male||2::male 11034
 
4.9%
0::female||1::male 8622
 
3.8%
0::female 7560
 
3.4%
0::male||1::female 4485
 
2.0%
1::male 4098
 
1.8%
0::male||1::male||2::male||3::male 3657
 
1.6%
0::female||1::male||2::male 1663
 
0.7%
0::male||1::female||2::male 1390
 
0.6%
Other values (613) 14213
 
6.3%
2023-11-25T22:21:05.434721image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 695213
25.2%
e 384917
13.9%
a 350230
12.7%
l 350230
12.7%
M 315543
11.4%
| 247573
 
9.0%
0 218255
 
7.9%
1 87886
 
3.2%
m 34687
 
1.3%
F 34686
 
1.3%
Other values (11) 44313
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1120065
40.5%
Other Punctuation 695214
25.2%
Decimal Number 350451
 
12.7%
Uppercase Letter 350229
 
12.7%
Math Symbol 247573
 
9.0%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 218255
62.3%
1 87886
25.1%
2 28268
 
8.1%
3 10210
 
2.9%
4 3568
 
1.0%
5 1294
 
0.4%
6 511
 
0.1%
7 248
 
0.1%
8 131
 
< 0.1%
9 80
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
e 384917
34.4%
a 350230
31.3%
l 350230
31.3%
m 34687
 
3.1%
f 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
: 695213
> 99.9%
, 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
M 315543
90.1%
F 34686
 
9.9%
Math Symbol
ValueCountFrequency (%)
| 247573
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1470294
53.2%
Common 1293239
46.8%

Most frequent character per script

Common
ValueCountFrequency (%)
: 695213
53.8%
| 247573
 
19.1%
0 218255
 
16.9%
1 87886
 
6.8%
2 28268
 
2.2%
3 10210
 
0.8%
4 3568
 
0.3%
5 1294
 
0.1%
6 511
 
< 0.1%
7 248
 
< 0.1%
Other values (4) 213
 
< 0.1%
Latin
ValueCountFrequency (%)
e 384917
26.2%
a 350230
23.8%
l 350230
23.8%
M 315543
21.5%
m 34687
 
2.4%
F 34686
 
2.4%
f 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2763533
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 695213
25.2%
e 384917
13.9%
a 350230
12.7%
l 350230
12.7%
M 315543
11.4%
| 247573
 
9.0%
0 218255
 
7.9%
1 87886
 
3.2%
m 34687
 
1.3%
F 34686
 
1.3%
Other values (11) 44313
 
1.6%
Distinct103136
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2023-11-25T22:21:05.885568image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length724
Median length7
Mean length17.070053
Min length4

Characters and Unicode

Total characters3845405
Distinct characters94
Distinct categories15 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100392 ?
Unique (%)44.6%

Sample

1st row0::Moses Malone||1::Wesley Jamal Brown
2nd row0::Officer||1::Eugene Taylor
3rd row0::D'aja Robinson||1::Shamel Capers||2::Kevin McClinton
4th row0::Leo Duchnowski
5th row0::Anthony Smith Jr||1::Mulijah Smart
ValueCountFrequency (%)
unknown 118417
 
26.8%
jr 3908
 
0.9%
0::michael 1932
 
0.4%
lee 1739
 
0.4%
williams 1669
 
0.4%
d 1661
 
0.4%
l 1632
 
0.4%
johnson 1525
 
0.3%
a 1467
 
0.3%
smith 1463
 
0.3%
Other values (101532) 306125
69.3%
2023-11-25T22:21:06.597705image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 530532
 
13.8%
: 310274
 
8.1%
o 265898
 
6.9%
e 224713
 
5.8%
217820
 
5.7%
a 211334
 
5.5%
r 172476
 
4.5%
k 141234
 
3.7%
i 136523
 
3.6%
w 136388
 
3.5%
Other values (84) 1498213
39.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2539036
66.0%
Uppercase Letter 501595
 
13.0%
Other Punctuation 328056
 
8.5%
Space Separator 217821
 
5.7%
Decimal Number 156702
 
4.1%
Math Symbol 98174
 
2.6%
Dash Punctuation 2955
 
0.1%
Final Punctuation 658
 
< 0.1%
Initial Punctuation 315
 
< 0.1%
Close Punctuation 40
 
< 0.1%
Other values (5) 53
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 530532
20.9%
o 265898
10.5%
e 224713
8.9%
a 211334
 
8.3%
r 172476
 
6.8%
k 141234
 
5.6%
i 136523
 
5.4%
w 136388
 
5.4%
l 118575
 
4.7%
s 100067
 
3.9%
Other values (19) 501296
19.7%
Uppercase Letter
ValueCountFrequency (%)
U 118930
23.7%
J 42262
 
8.4%
M 32613
 
6.5%
D 31331
 
6.2%
C 27370
 
5.5%
S 25516
 
5.1%
A 24714
 
4.9%
R 24005
 
4.8%
B 22182
 
4.4%
T 19628
 
3.9%
Other values (17) 133044
26.5%
Decimal Number
ValueCountFrequency (%)
0 89898
57.4%
1 45070
28.8%
2 13819
 
8.8%
3 4920
 
3.1%
4 1751
 
1.1%
5 638
 
0.4%
6 287
 
0.2%
7 148
 
0.1%
9 86
 
0.1%
8 85
 
0.1%
Other Punctuation
ValueCountFrequency (%)
: 310274
94.6%
. 13264
 
4.0%
" 2308
 
0.7%
, 1192
 
0.4%
' 978
 
0.3%
/ 34
 
< 0.1%
& 3
 
< 0.1%
* 2
 
< 0.1%
1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 2951
99.9%
3
 
0.1%
1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
217820
> 99.9%
  1
 
< 0.1%
Final Punctuation
ValueCountFrequency (%)
354
53.8%
304
46.2%
Initial Punctuation
ValueCountFrequency (%)
306
97.1%
9
 
2.9%
Close Punctuation
ValueCountFrequency (%)
) 39
97.5%
] 1
 
2.5%
Open Punctuation
ValueCountFrequency (%)
( 39
97.5%
[ 1
 
2.5%
Format
ValueCountFrequency (%)
­ 6
85.7%
 1
 
14.3%
Math Symbol
ValueCountFrequency (%)
| 98174
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 4
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3040631
79.1%
Common 804774
 
20.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 530532
17.4%
o 265898
 
8.7%
e 224713
 
7.4%
a 211334
 
7.0%
r 172476
 
5.7%
k 141234
 
4.6%
i 136523
 
4.5%
w 136388
 
4.5%
U 118930
 
3.9%
l 118575
 
3.9%
Other values (46) 984028
32.4%
Common
ValueCountFrequency (%)
: 310274
38.6%
217820
27.1%
| 98174
 
12.2%
0 89898
 
11.2%
1 45070
 
5.6%
2 13819
 
1.7%
. 13264
 
1.6%
3 4920
 
0.6%
- 2951
 
0.4%
" 2308
 
0.3%
Other values (28) 6276
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3844406
> 99.9%
Punctuation 978
 
< 0.1%
None 21
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 530532
 
13.8%
: 310274
 
8.1%
o 265898
 
6.9%
e 224713
 
5.8%
217820
 
5.7%
a 211334
 
5.5%
r 172476
 
4.5%
k 141234
 
3.7%
i 136523
 
3.6%
w 136388
 
3.5%
Other values (70) 1497214
38.9%
Punctuation
ValueCountFrequency (%)
354
36.2%
306
31.3%
304
31.1%
9
 
0.9%
3
 
0.3%
1
 
0.1%
1
 
0.1%
None
ValueCountFrequency (%)
ñ 10
47.6%
­ 6
28.6%
Á 1
 
4.8%
  1
 
4.8%
ç 1
 
4.8%
 1
 
4.8%
ó 1
 
4.8%
Distinct234
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2023-11-25T22:21:06.902861image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length366
Median length7
Mean length8.2516691
Min length7

Characters and Unicode

Total characters1858870
Distinct characters52
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)< 0.1%

Sample

1st rowUnknown
2nd rowUnknown
3rd rowUnknown
4th rowUnknown
5th rowUnknown
ValueCountFrequency (%)
unknown 212002
82.0%
robbery 4461
 
1.7%
4451
 
1.7%
1::armed 3386
 
1.3%
others 2654
 
1.0%
current 2654
 
1.0%
or 2654
 
1.0%
former 2642
 
1.0%
1::significant 2007
 
0.8%
1::family 1967
 
0.8%
Other values (172) 19741
 
7.6%
2023-11-25T22:21:07.456724image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 653189
35.1%
o 236224
 
12.7%
w 213882
 
11.5%
k 212126
 
11.4%
U 212002
 
11.4%
: 35396
 
1.9%
r 34666
 
1.9%
33347
 
1.8%
e 30547
 
1.6%
i 18428
 
1.0%
Other values (42) 179063
 
9.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1511547
81.3%
Uppercase Letter 247398
 
13.3%
Other Punctuation 35396
 
1.9%
Space Separator 33347
 
1.8%
Decimal Number 17723
 
1.0%
Math Symbol 8884
 
0.5%
Dash Punctuation 4575
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 653189
43.2%
o 236224
 
15.6%
w 213882
 
14.1%
k 212126
 
14.0%
r 34666
 
2.3%
e 30547
 
2.0%
i 18428
 
1.2%
m 16334
 
1.1%
b 15736
 
1.0%
t 11979
 
0.8%
Other values (13) 68436
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
U 212002
85.7%
A 8490
 
3.4%
R 7592
 
3.1%
F 3540
 
1.4%
S 2654
 
1.1%
N 1871
 
0.8%
P 1756
 
0.7%
V 1756
 
0.7%
K 1756
 
0.7%
H 1753
 
0.7%
Other values (5) 4228
 
1.7%
Decimal Number
ValueCountFrequency (%)
1 10622
59.9%
2 3181
 
17.9%
0 2192
 
12.4%
3 1166
 
6.6%
4 376
 
2.1%
5 116
 
0.7%
6 38
 
0.2%
7 15
 
0.1%
8 10
 
0.1%
9 7
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
: 35396
100.0%
Space Separator
ValueCountFrequency (%)
33347
100.0%
Math Symbol
ValueCountFrequency (%)
| 8884
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4575
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1758945
94.6%
Common 99925
 
5.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 653189
37.1%
o 236224
 
13.4%
w 213882
 
12.2%
k 212126
 
12.1%
U 212002
 
12.1%
r 34666
 
2.0%
e 30547
 
1.7%
i 18428
 
1.0%
m 16334
 
0.9%
b 15736
 
0.9%
Other values (28) 115811
 
6.6%
Common
ValueCountFrequency (%)
: 35396
35.4%
33347
33.4%
1 10622
 
10.6%
| 8884
 
8.9%
- 4575
 
4.6%
2 3181
 
3.2%
0 2192
 
2.2%
3 1166
 
1.2%
4 376
 
0.4%
5 116
 
0.1%
Other values (4) 70
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1858870
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 653189
35.1%
o 236224
 
12.7%
w 213882
 
11.5%
k 212126
 
11.4%
U 212002
 
11.4%
: 35396
 
1.9%
r 34666
 
1.9%
33347
 
1.8%
e 30547
 
1.6%
i 18428
 
1.0%
Other values (42) 179063
 
9.6%
Distinct1369
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2023-11-25T22:21:07.711214image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length1066
Median length636
Mean length21.717342
Min length8

Characters and Unicode

Total characters4892309
Distinct characters31
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique694 ?
Unique (%)0.3%

Sample

1st row0::Killed||1::Unharmed, Arrested
2nd row0::Injured||1::Injured
3rd row0::Killed||1::Arrested||2::Arrested
4th row0::Injured
5th row0::Killed||1::Unharmed, Arrested
ValueCountFrequency (%)
0::injured 71060
23.0%
arrested 58626
19.0%
0::unharmed 44771
14.5%
0::injured||1::unharmed 21638
 
7.0%
0::killed 20683
 
6.7%
0::killed||1::unharmed 13942
 
4.5%
0::unharmed||1::unharmed 9496
 
3.1%
arrested||1::unharmed 8414
 
2.7%
arrested||2::unharmed 7637
 
2.5%
0::injured||1::injured 6375
 
2.1%
Other values (663) 45690
14.8%
2023-11-25T22:21:08.202142image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 723627
14.8%
e 540172
11.0%
r 494100
 
10.1%
d 447860
 
9.2%
n 309476
 
6.3%
| 276129
 
5.6%
0 221882
 
4.5%
U 180029
 
3.7%
h 180029
 
3.7%
a 180029
 
3.7%
Other values (21) 1338976
27.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2913429
59.6%
Other Punctuation 806687
 
16.5%
Uppercase Letter 447860
 
9.2%
Decimal Number 365144
 
7.5%
Math Symbol 276129
 
5.6%
Space Separator 83060
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 540172
18.5%
r 494100
17.0%
d 447860
15.4%
n 309476
10.6%
h 180029
 
6.2%
a 180029
 
6.2%
m 180029
 
6.2%
j 129447
 
4.4%
u 129447
 
4.4%
t 92312
 
3.2%
Other values (3) 230528
7.9%
Decimal Number
ValueCountFrequency (%)
0 221882
60.8%
1 94302
25.8%
2 30758
 
8.4%
3 11343
 
3.1%
4 4098
 
1.1%
5 1525
 
0.4%
6 632
 
0.2%
7 320
 
0.1%
8 170
 
< 0.1%
9 114
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
U 180029
40.2%
I 129447
28.9%
A 92312
20.6%
K 46072
 
10.3%
Other Punctuation
ValueCountFrequency (%)
: 723627
89.7%
, 83060
 
10.3%
Math Symbol
ValueCountFrequency (%)
| 276129
100.0%
Space Separator
ValueCountFrequency (%)
83060
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3361289
68.7%
Common 1531020
31.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 540172
16.1%
r 494100
14.7%
d 447860
13.3%
n 309476
9.2%
U 180029
 
5.4%
h 180029
 
5.4%
a 180029
 
5.4%
m 180029
 
5.4%
I 129447
 
3.9%
j 129447
 
3.9%
Other values (7) 590671
17.6%
Common
ValueCountFrequency (%)
: 723627
47.3%
| 276129
 
18.0%
0 221882
 
14.5%
1 94302
 
6.2%
83060
 
5.4%
, 83060
 
5.4%
2 30758
 
2.0%
3 11343
 
0.7%
4 4098
 
0.3%
5 1525
 
0.1%
Other values (4) 1236
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4892309
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 723627
14.8%
e 540172
11.0%
r 494100
 
10.1%
d 447860
 
9.2%
n 309476
 
6.3%
| 276129
 
5.6%
0 221882
 
4.5%
U 180029
 
3.7%
h 180029
 
3.7%
a 180029
 
3.7%
Other values (21) 1338976
27.4%
Distinct211
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2023-11-25T22:21:08.456797image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length1080
Median length723
Mean length24.622962
Min length8

Characters and Unicode

Total characters5546864
Distinct characters25
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)< 0.1%

Sample

1st row0::Victim||1::Subject-Suspect
2nd row0::Victim||1::Subject-Suspect
3rd row0::Victim||1::Subject-Suspect||2::Subject-Suspect
4th row0::Subject-Suspect
5th row0::Victim||1::Subject-Suspect
ValueCountFrequency (%)
0::subject-suspect 68420
30.4%
0::victim 57785
25.7%
0::victim||1::subject-suspect 46958
20.8%
0::victim||1::subject-suspect||2::subject-suspect 10609
 
4.7%
0::subject-suspect||1::subject-suspect 8689
 
3.9%
0::victim||1::victim 7949
 
3.5%
0::victim||1::victim||2::subject-suspect 5205
 
2.3%
0::victim||1::subject-suspect||2::subject-suspect||3::subject-suspect 3580
 
1.6%
0::subject-suspect||1::subject-suspect||2::subject-suspect 2919
 
1.3%
0::victim||1::victim||2::subject-suspect||3::subject-suspect 1852
 
0.8%
Other values (201) 11306
 
5.0%
2023-11-25T22:21:08.951631image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 742875
13.4%
c 584135
10.5%
t 584135
10.5%
S 419238
 
7.6%
u 419238
 
7.6%
e 419238
 
7.6%
i 329794
 
5.9%
| 295436
 
5.3%
0 225351
 
4.1%
b 209619
 
3.8%
Other values (15) 1317805
23.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3339913
60.2%
Other Punctuation 742875
 
13.4%
Uppercase Letter 584135
 
10.5%
Decimal Number 374886
 
6.8%
Math Symbol 295436
 
5.3%
Dash Punctuation 209619
 
3.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 584135
17.5%
t 584135
17.5%
u 419238
12.6%
e 419238
12.6%
i 329794
9.9%
b 209619
 
6.3%
j 209619
 
6.3%
s 209619
 
6.3%
p 209619
 
6.3%
m 164897
 
4.9%
Decimal Number
ValueCountFrequency (%)
0 225351
60.1%
1 98061
26.2%
2 32236
 
8.6%
3 11968
 
3.2%
4 4337
 
1.2%
5 1621
 
0.4%
6 676
 
0.2%
7 336
 
0.1%
8 181
 
< 0.1%
9 119
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
S 419238
71.8%
V 164897
 
28.2%
Other Punctuation
ValueCountFrequency (%)
: 742875
100.0%
Math Symbol
ValueCountFrequency (%)
| 295436
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 209619
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3924048
70.7%
Common 1622816
29.3%

Most frequent character per script

Common
ValueCountFrequency (%)
: 742875
45.8%
| 295436
 
18.2%
0 225351
 
13.9%
- 209619
 
12.9%
1 98061
 
6.0%
2 32236
 
2.0%
3 11968
 
0.7%
4 4337
 
0.3%
5 1621
 
0.1%
6 676
 
< 0.1%
Other values (3) 636
 
< 0.1%
Latin
ValueCountFrequency (%)
c 584135
14.9%
t 584135
14.9%
S 419238
10.7%
u 419238
10.7%
e 419238
10.7%
i 329794
8.4%
b 209619
 
5.3%
j 209619
 
5.3%
s 209619
 
5.3%
p 209619
 
5.3%
Other values (2) 329794
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5546864
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 742875
13.4%
c 584135
10.5%
t 584135
10.5%
S 419238
 
7.6%
u 419238
 
7.6%
e 419238
 
7.6%
i 329794
 
5.9%
| 295436
 
5.3%
0 225351
 
4.1%
b 209619
 
3.8%
Other values (15) 1317805
23.8%
Distinct203418
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2023-11-25T22:21:09.355590image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length3015
Median length1144
Mean length128.78871
Min length7

Characters and Unicode

Total characters29012490
Distinct characters86
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique194847 ?
Unique (%)86.5%

Sample

1st rowhttp://articles.baltimoresun.com/2013-05-06/news/bs-md-ci-triple-shooting-20130506_1_multiple-gunshot-wounds-baltimore-police-three-suspects||http://abcnews.go.com/US/wireStory/baltimore-gang-member-admits-killing-witness-2013-51040451
2nd rowhttp://www.burlingtoncountytimes.com/news/20171214/man-charged-in-shooting-incident-with-delanco-cop-not-guilty-by-reason-of-insanity
3rd rowhttp://newyork.cbslocal.com/2014/07/30/second-suspect-charged-in-queens-shooting-that-killed-girl-14-on-bus-last-year/||http://qns.com/story/2017/06/22/second-shooter-convicted-fatally-shooting-jamaica-teenager-riding-bus/
4th rowhttps://patch.com/new-york/glencove/update-police-shoot-drug-suspect-in-locust-valley||https://patch.com/new-york/glencove/drug-suspect-shot-by-police-idd
5th rowhttp://www.nj.com/hudson/index.ssf/2018/01/murder_trial_of_man_killed_outside_jersey_city_par.html#incart_river_index
ValueCountFrequency (%)
http://blog.tsa.gov 1179
 
0.5%
http://callsforservice.jaxsheriff.org 802
 
0.4%
unknown 597
 
0.3%
https://data.oaklandnet.com/public-safety/crimewatch-maps-past-90-days/ym6k-rx7a 491
 
0.2%
http://itmdapps.ci.mil.wi.us/mpdcalldata/currentcadcalls/callsservice.faces 327
 
0.1%
http://www.springsgov.com/units/police/policeblotter.asp 219
 
0.1%
https://www.facebook.com/pg/policeclips/posts/?ref=page_internal 124
 
0.1%
http://www.tampabay.com/news/hillsborough/crime 107
 
< 0.1%
http://blog.tsa.gov/search 87
 
< 0.1%
https://www.montereysheriff.org/mcsologs/dpl.pdf 82
 
< 0.1%
Other values (203401) 221257
98.2%
2023-11-25T22:21:09.948609image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 1999870
 
6.9%
- 1981828
 
6.8%
e 1900690
 
6.6%
/ 1857464
 
6.4%
o 1700038
 
5.9%
n 1474133
 
5.1%
s 1355074
 
4.7%
i 1306534
 
4.5%
a 1297600
 
4.5%
w 1135220
 
3.9%
Other values (76) 13004039
44.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 20708441
71.4%
Other Punctuation 2891663
 
10.0%
Decimal Number 2851378
 
9.8%
Dash Punctuation 1981828
 
6.8%
Uppercase Letter 216526
 
0.7%
Math Symbol 194800
 
0.7%
Connector Punctuation 167726
 
0.6%
Open Punctuation 59
 
< 0.1%
Close Punctuation 59
 
< 0.1%
Currency Symbol 10
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1999870
 
9.7%
e 1900690
 
9.2%
o 1700038
 
8.2%
n 1474133
 
7.1%
s 1355074
 
6.5%
i 1306534
 
6.3%
a 1297600
 
6.3%
w 1135220
 
5.5%
r 1115246
 
5.4%
c 1082763
 
5.2%
Other values (16) 6341273
30.6%
Uppercase Letter
ValueCountFrequency (%)
S 24756
 
11.4%
P 17574
 
8.1%
C 14912
 
6.9%
N 13952
 
6.4%
M 12870
 
5.9%
D 12818
 
5.9%
A 11740
 
5.4%
W 11708
 
5.4%
E 10441
 
4.8%
F 8813
 
4.1%
Other values (16) 76942
35.5%
Other Punctuation
ValueCountFrequency (%)
/ 1857464
64.2%
. 676683
 
23.4%
: 307364
 
10.6%
# 15050
 
0.5%
? 12170
 
0.4%
& 10764
 
0.4%
% 8336
 
0.3%
, 3219
 
0.1%
! 406
 
< 0.1%
; 178
 
< 0.1%
Other values (3) 29
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 480647
16.9%
0 452726
15.9%
2 410399
14.4%
3 238046
8.3%
5 233843
8.2%
4 222052
7.8%
6 218428
7.7%
7 215948
7.6%
8 191910
 
6.7%
9 187379
 
6.6%
Math Symbol
ValueCountFrequency (%)
| 162128
83.2%
= 22854
 
11.7%
+ 9784
 
5.0%
~ 34
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
[ 44
74.6%
( 15
 
25.4%
Close Punctuation
ValueCountFrequency (%)
] 44
74.6%
) 15
 
25.4%
Dash Punctuation
ValueCountFrequency (%)
- 1981828
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 167726
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20924967
72.1%
Common 8087523
 
27.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1999870
 
9.6%
e 1900690
 
9.1%
o 1700038
 
8.1%
n 1474133
 
7.0%
s 1355074
 
6.5%
i 1306534
 
6.2%
a 1297600
 
6.2%
w 1135220
 
5.4%
r 1115246
 
5.3%
c 1082763
 
5.2%
Other values (42) 6557799
31.3%
Common
ValueCountFrequency (%)
- 1981828
24.5%
/ 1857464
23.0%
. 676683
 
8.4%
1 480647
 
5.9%
0 452726
 
5.6%
2 410399
 
5.1%
: 307364
 
3.8%
3 238046
 
2.9%
5 233843
 
2.9%
4 222052
 
2.7%
Other values (24) 1226471
15.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29012490
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 1999870
 
6.9%
- 1981828
 
6.8%
e 1900690
 
6.6%
/ 1857464
 
6.4%
o 1700038
 
5.9%
n 1474133
 
5.1%
s 1355074
 
4.7%
i 1306534
 
4.5%
a 1297600
 
4.5%
w 1135220
 
3.9%
Other values (76) 13004039
44.8%

state_house_district
Real number (ℝ)

Distinct276
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.687267
Minimum-1
Maximum901
Zeros0
Zeros (%)0.0%
Negative4283
Negative (%)1.9%
Memory size3.4 MiB
2023-11-25T22:21:10.158973image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile3
Q121
median48
Q391
95-th percentile139
Maximum901
Range902
Interquartile range (IQR)70

Descriptive statistics

Standard deviation50.940856
Coefficient of variation (CV)0.86800525
Kurtosis28.328955
Mean58.687267
Median Absolute Deviation (MAD)32
Skewness3.4187283
Sum13220598
Variance2594.9708
MonotonicityNot monotonic
2023-11-25T22:21:10.375042image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
95 8783
 
3.9%
111 5605
 
2.5%
41 4803
 
2.1%
20 4316
 
1.9%
-1 4283
 
1.9%
18 4157
 
1.8%
10 4079
 
1.8%
141 4000
 
1.8%
40 3724
 
1.7%
34 3274
 
1.5%
Other values (266) 178248
79.1%
ValueCountFrequency (%)
-1 4283
1.9%
1 1924
0.9%
2 2791
1.2%
3 2951
1.3%
4 1982
0.9%
5 2444
1.1%
6 2664
1.2%
7 1922
0.9%
8 2336
1.0%
9 2318
1.0%
ValueCountFrequency (%)
901 1
< 0.1%
814 1
< 0.1%
813 1
< 0.1%
811 1
< 0.1%
809 1
< 0.1%
808 1
< 0.1%
805 1
< 0.1%
804 1
< 0.1%
801 1
< 0.1%
729 2
< 0.1%

state_senate_district
Real number (ℝ)

Distinct68
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.91714
Minimum-1
Maximum67
Zeros0
Zeros (%)0.0%
Negative444
Negative (%)0.2%
Memory size3.4 MiB
2023-11-25T22:21:10.575186image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile1
Q16
median17
Q331
95-th percentile47
Maximum67
Range68
Interquartile range (IQR)25

Descriptive statistics

Standard deviation14.885908
Coefficient of variation (CV)0.74739186
Kurtosis-0.37644999
Mean19.91714
Median Absolute Deviation (MAD)12
Skewness0.63945565
Sum4486774
Variance221.59027
MonotonicityNot monotonic
2023-11-25T22:21:10.793924image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 14747
 
6.5%
5 11359
 
5.0%
1 11075
 
4.9%
9 8524
 
3.8%
33 8087
 
3.6%
2 6852
 
3.0%
4 6850
 
3.0%
11 5854
 
2.6%
15 5754
 
2.6%
6 5671
 
2.5%
Other values (58) 140499
62.4%
ValueCountFrequency (%)
-1 444
 
0.2%
1 11075
4.9%
2 6852
3.0%
3 14747
6.5%
4 6850
3.0%
5 11359
5.0%
6 5671
 
2.5%
7 4466
 
2.0%
8 3803
 
1.7%
9 8524
3.8%
ValueCountFrequency (%)
67 66
 
< 0.1%
66 31
 
< 0.1%
65 120
 
0.1%
64 19
 
< 0.1%
63 1145
0.5%
62 336
 
0.1%
61 170
 
0.1%
60 197
 
0.1%
59 1020
0.5%
58 259
 
0.1%

Interactions

2023-11-25T22:20:46.607084image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:40.223200image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:41.212304image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:42.290149image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:43.495758image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:44.545832image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:45.550140image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:46.764686image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:40.354799image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:41.357812image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:42.445073image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:43.646448image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:44.688670image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:45.696760image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:46.928215image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:40.496990image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:41.504590image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:42.730334image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:43.802722image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:44.827560image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:45.850657image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:47.088013image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:40.640082image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:41.654152image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:42.887757image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:43.960935image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:44.972692image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:46.002606image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:47.249432image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:40.783961image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:41.802999image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:43.040565image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:44.106574image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:45.112378image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:46.153030image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:47.405916image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:40.921352image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:41.962786image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:43.189494image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:44.252105image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:45.254520image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:46.301603image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:47.593526image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:41.057413image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:42.125798image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:43.336573image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:44.388673image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:45.393179image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-11-25T22:20:46.445274image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Correlations

2023-11-25T22:21:10.948468image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
congressional_districtincident_idlatitudelongituden_guns_involvedn_injuredn_killedstate_house_districtstate_senate_district
congressional_district1.0000.004-0.155-0.0320.0010.0340.0780.2310.268
incident_id0.0041.0000.025-0.0200.1010.0390.017-0.024-0.001
latitude-0.1550.0251.0000.1540.0360.0450.104-0.213-0.079
longitude-0.032-0.0200.1541.0000.0080.0600.0570.214-0.012
n_guns_involved0.0010.1010.0360.0081.0000.0610.0540.001-0.004
n_injured0.0340.0390.0450.0600.0611.0000.265-0.034-0.044
n_killed0.0780.0170.1040.0570.0540.2651.0000.0010.001
state_house_district0.231-0.024-0.2130.2140.001-0.0340.0011.0000.270
state_senate_district0.268-0.001-0.079-0.012-0.004-0.0440.0010.2701.000

Missing values

2023-11-25T22:20:48.028533image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
A simple visualization of nullity by column.
2023-11-25T22:20:49.206659image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

incident_iddatestatecity_or_countyaddressn_killedn_injuredincident_urlsource_urlincident_url_fields_missingcongressional_districtgun_stolengun_typeincident_characteristicslatitudelocation_descriptionlongituden_guns_involvednotesparticipant_ageparticipant_age_groupparticipant_genderparticipant_nameparticipant_relationshipparticipant_statusparticipant_typesourcesstate_house_districtstate_senate_district
639843532013-05-02MarylandBaltimore600 block of Cokesbury Ave10http://www.gunviolencearchive.org/incident/984353http://abcnews.go.com/US/wireStory/baltimore-gang-member-admits-killing-witness-2013-51040451False7.00::Unknown0::UnknownShot - Dead (murder, accidental, suicide)||Gang involvement||Drug involvement39.3167Unknown-76.60851.0Black Guerilla Family gang0::22||1::250::Adult 18+||1::Adult 18+0::Male||1::Male0::Moses Malone||1::Wesley Jamal BrownUnknown0::Killed||1::Unharmed, Arrested0::Victim||1::Subject-Suspecthttp://articles.baltimoresun.com/2013-05-06/news/bs-md-ci-triple-shooting-20130506_1_multiple-gunshot-wounds-baltimore-police-three-suspects||http://abcnews.go.com/US/wireStory/baltimore-gang-member-admits-killing-witness-2013-5104045143.043.0
7510077852013-05-14New JerseyDelancoDelaware Ave02http://www.gunviolencearchive.org/incident/1007785http://www.burlingtoncountytimes.com/news/20171214/man-charged-in-shooting-incident-with-delanco-cop-not-guilty-by-reason-of-insanityFalse3.00::Unknown0::UnknownShot - Wounded/Injured||Officer Involved Incident||Officer Involved Shooting - Officer shot||Officer Involved Shooting - subject/suspect/perpetrator shot40.0521Unknown-74.95781.0scuffle during arrest led to suspect being shot 4 times and officer being shot once with his own gun1::221::Adult 18+0::Male||1::Male0::Officer||1::Eugene TaylorUnknown0::Injured||1::Injured0::Victim||1::Subject-Suspecthttp://www.burlingtoncountytimes.com/news/20171214/man-charged-in-shooting-incident-with-delanco-cop-not-guilty-by-reason-of-insanity7.07.0
788735752013-05-18New YorkJamaicaSutphin Blvd and Rockaway Blvd10http://www.gunviolencearchive.org/incident/873575http://qns.com/story/2017/06/22/second-shooter-convicted-fatally-shooting-jamaica-teenager-riding-bus/False5.00::Unknown0::UnknownShot - Dead (murder, accidental, suicide)||Gang involvement||Possession of gun by felon or prohibited person40.6730Unknown-73.78811.0Girl shot dead while riding MTA Q6 Bus; vic was unintended target of gang related shooting;\r\r\n40.673074, -73.787983 ;0::14||1::15||2::210::Teen 12-17||1::Teen 12-17||2::Adult 18+0::Female||1::Male||2::Male0::D'aja Robinson||1::Shamel Capers||2::Kevin McClintonUnknown0::Killed||1::Arrested||2::Arrested0::Victim||1::Subject-Suspect||2::Subject-Suspecthttp://newyork.cbslocal.com/2014/07/30/second-suspect-charged-in-queens-shooting-that-killed-girl-14-on-bus-last-year/||http://qns.com/story/2017/06/22/second-shooter-convicted-fatally-shooting-jamaica-teenager-riding-bus/32.010.0
1218932512013-07-01New YorkLocust Valley99 Horse Hollow Rd01http://www.gunviolencearchive.org/incident/893251https://patch.com/new-york/glencove/drug-suspect-shot-by-police-iddFalse3.00::Unknown0::UnknownShot - Wounded/Injured||Officer Involved Incident||Officer Involved Shooting - subject/suspect/perpetrator shot||Drug involvement40.8880Unknown-73.58991.0Traffic stop; backed car into approaching officer, knocked him to ground0::220::Adult 18+0::Male0::Leo DuchnowskiUnknown0::Injured0::Subject-Suspecthttps://patch.com/new-york/glencove/update-police-shoot-drug-suspect-in-locust-valley||https://patch.com/new-york/glencove/drug-suspect-shot-by-police-idd13.05.0
12310239082013-07-02New JerseyJersey CityDwight St10http://www.gunviolencearchive.org/incident/1023908http://www.nj.com/hudson/index.ssf/2018/01/murder_trial_of_man_killed_outside_jersey_city_par.html#incart_river_indexFalse10.00::Unknown0::UnknownShot - Dead (murder, accidental, suicide)||House party40.7037Unknown-74.08401.0No Notes0::21||1::190::Adult 18+||1::Adult 18+0::Male||1::Male0::Anthony Smith Jr||1::Mulijah SmartUnknown0::Killed||1::Unharmed, Arrested0::Victim||1::Subject-Suspecthttp://www.nj.com/hudson/index.ssf/2018/01/murder_trial_of_man_killed_outside_jersey_city_par.html#incart_river_index31.031.0
1609645732013-08-05PennsylvaniaPhiladelphia5100 Parrish St10http://www.gunviolencearchive.org/incident/964573http://www.philly.com/philly/news/crime/feds-charge-13-in-w-philly-drug-gang-war-20171019.htmlFalse2.00::Unknown0::UnknownShot - Dead (murder, accidental, suicide)||Gang involvement||Drug involvement39.9669West Mill Creek Playground-75.22291.0Grounds gang vic selling crack on rival gang (Pit) territory1::300::Adult 18+||1::Adult 18+0::Male||1::Male0::Brian Littles||1::Bryant CallowayUnknown0::Killed||1::Arrested0::Victim||1::Subject-Suspecthttp://www.philly.com/philly/news/crime/feds-charge-13-in-w-philly-drug-gang-war-20171019.html190.07.0
17010746132013-08-17PennsylvaniaYork376 Walnut St10http://www.gunviolencearchive.org/incident/1074613https://www.ydr.com/story/news/local/2018/03/21/york-county-jury-delivers-million-dollar-verdict-against-georges-tavern-security-negligence-murder/444774002/False4.00::Unknown0::UnknownShot - Dead (murder, accidental, suicide)||Institution/Group/Business||Bar/club incident - in or around establishment39.9672George's Tavern-76.72061.0vic shot in back while breaking up a bar fight1::250::Adult 18+||1::Adult 18+0::Male||1::Male0::Jaime "Butter" Sanabria||1::Halim "Buddha" BowenUnknown0::Killed||1::Unharmed, Arrested0::Victim||1::Subject-Suspecthttps://www.ydr.com/story/news/local/2018/03/21/york-county-jury-delivers-million-dollar-verdict-against-georges-tavern-security-negligence-murder/444774002/95.028.0
1789580322013-08-23New JerseyTrentonMiddle Rose St and Brunswick Ave10http://www.gunviolencearchive.org/incident/958032http://trenton.homicidewatch.org/2017/10/12/gunman-who-killed-trenton-rapper-young-farr-pleads-guilty/False10.00::Unknown0::HandgunShot - Dead (murder, accidental, suicide)40.2281Unknown-74.76111.0vic shot twice in head0::26||1::390::Adult 18+||1::Adult 18+0::Male||1::Male0::Jafar "Young Farr" Lewis||1::Wayne BushUnknown0::Killed||1::Arrested0::Victim||1::Subject-Suspecthttp://trenton.homicidewatch.org/2017/10/12/gunman-who-killed-trenton-rapper-young-farr-pleads-guilty/15.015.0
2126709642013-10-05IndianaFort Wayne2020 Hobson Rd11http://www.gunviolencearchive.org/incident/670964http://www.21alive.com/news/local/Hobson-Rd-Shooting-Victim-In-Critical-Condition-226489941.htmlFalse3.00::Unknown0::UnknownShot - Wounded/Injured||Shot - Dead (murder, accidental, suicide)41.0951Baldwin Creek Apartment Complex-85.09841.0Victim climbed out window, fell to ground after being shot; died at hospital; 2nd victim probable bystander;0::210::Adult 18+||1::Adult 18+0::Male||1::Male0::Johnny Lee UpshawUnknown0::Killed||1::Injured0::Victim||1::Victimhttp://www.21alive.com/news/local/Hobson-Rd-Shooting-Victim-In-Critical-Condition-226489941.html85.015.0
2179849652013-10-07New JerseyTabernacleUS 20610http://www.gunviolencearchive.org/incident/984965http://www.burlingtoncountytimes.com/news/20171109/trenton-man-resentenced-to-life-for-tabernacle-murderFalse3.00::Unknown0::UnknownShot - Dead (murder, accidental, suicide)||Kidnapping/abductions/hostage39.8461Unknown-74.73481.0vic kidnapped and shot twice0::47||1::370::Adult 18+||1::Adult 18+0::Female||1::Male0::Lisa Armstrong||1::Terrance PattersonUnknown0::Killed||1::Unharmed, Arrested0::Victim||1::Subject-Suspecthttp://www.burlingtoncountytimes.com/news/20171109/trenton-man-resentenced-to-life-for-tabernacle-murder9.09.0
incident_iddatestatecity_or_countyaddressn_killedn_injuredincident_urlsource_urlincident_url_fields_missingcongressional_districtgun_stolengun_typeincident_characteristicslatitudelocation_descriptionlongituden_guns_involvednotesparticipant_ageparticipant_age_groupparticipant_genderparticipant_nameparticipant_relationshipparticipant_statusparticipant_typesourcesstate_house_districtstate_senate_district
23966510822262018-03-31MissouriSaint Clair1100 Park Dr01http://www.gunviolencearchive.org/incident/1082226http://fox2now.com/2018/04/01/franklin-county-swat-team-assists-after-shooting/False1.00::Unknown0::HandgunShot - Wounded/Injured||Officer Involved Incident||Officer Involved Incident - Weapon involved but no shots fired||Officer Involved Shooting - subject/suspect/perpetrator surrender at standoff||ATF/LE Confiscation/Raid/Arrest38.551992Unknown-91.7998891.0Victim shot in chest prior to police arrival; armed standoff ensued with no additional shots fired; gun recovered.0::31||1::560::Adult 18+||1::Adult 18+0::Male||1::MaleUnknownUnknown0::Injured||1::Unharmed, Arrested0::Victim||1::Subject-Suspecthttp://fox2now.com/2018/04/01/franklin-county-swat-team-assists-after-shooting/76.05.0
23966610818942018-03-31MissouriSaint Louis3100 block of California St10http://www.gunviolencearchive.org/incident/1081894http://www.stltoday.com/news/local/crime-and-courts/family-believes-st-louis-boy-was-looking-for-candy-when/article_d352935e-07e7-5ab0-84e9-e84d52be72fe.htmlFalse1.00::Unknown0::UnknownShot - Dead (murder, accidental, suicide)||Accidental Shooting||Accidental Shooting - Death||Accidental/Negligent Discharge||Playing with gun||Child Involved Incident||Child picked up & fired gun||Child killed by child38.551992Unknown-91.7998891.0Child fatally shot by younger brother.0::7||1::50::Child 0-11||1::Child 0-110::Male||1::Male0::Jermon Perry1::Family0::Killed||1::Unharmed0::Victim||1::Subject-Suspecthttp://fox2now.com/2018/03/31/7-year-old-dies-after-being-shot-in-he-head-in-south-st-louis/||http://www.stltoday.com/news/local/crime-and-courts/family-believes-st-louis-boy-was-looking-for-candy-when/article_d352935e-07e7-5ab0-84e9-e84d52be72fe.html76.05.0
23966810817422018-03-31MichiganDetroitI-9601http://www.gunviolencearchive.org/incident/1081742https://www.freep.com/story/news/local/michigan/wayne/2018/03/31/party-bus-shooting-detroit/475537002/False13.00::Unknown0::UnknownShot - Wounded/Injured||Drive-by (car to street, car to car)42.689842Unknown-83.9784751.0near Wyoming St0::290::Adult 18+0::MaleUnknownUnknown0::Injured0::Victimhttps://www.freep.com/story/news/local/michigan/wayne/2018/03/31/party-bus-shooting-detroit/475537002/34.027.0
23966910829902018-03-31WisconsinMadisonHayes Rd00http://www.gunviolencearchive.org/incident/1082990https://www.channel3000.com/news/crime/couple-finds-evidence-of-gunfire-after-reports-of-shots-fired-in-area/724111486False4.00::Unknown0::45 AutoShots Fired - No Injuries43.287695Unknown-88.5313471.0.45 shell casing recovered0::290::Adult 18+0::MaleUnknownUnknown0::Injured0::Subject-Suspecthttp://host.madison.com/wsj/news/local/crime/gunfire-reported-on-east-side-nobody-hurt-madison-police-say/article_a621b2db-60ff-5f00-94f6-b3aa80711e99.html||https://www.channel3000.com/news/crime/couple-finds-evidence-of-gunfire-after-reports-of-shots-fired-in-area/72411148616.06.0
23967010817522018-03-31IllinoisChicago1 block of N Paulina St01http://www.gunviolencearchive.org/incident/1081752https://chicago.suntimes.com/news/man-36-wounded-in-shooting-on-near-west-side/False7.00::Unknown0::UnknownShot - Wounded/Injured41.473079Unknown-88.1017511.0Rt. leg, good; walk-up by 1;0::360::Adult 18+||1::Adult 18+0::Male||1::MaleUnknownUnknown0::Injured||1::Unharmed0::Victim||1::Subject-Suspecthttps://chicago.suntimes.com/news/man-36-wounded-in-shooting-on-near-west-side/10.05.0
23967110820612018-03-31WashingtonSpokane (Spokane Valley)12600 block of N Willow Crest Ln00http://www.gunviolencearchive.org/incident/1082061https://www.kxly.com/news/domestic-violence-suspect-arrested-after-swat-team-standoff/723525275False5.00::Unknown0::UnknownNon-Shooting Incident||Possession (gun(s) found during commission of other crimes)47.663800Unknown-117.2350001.0DV call leads to seizure of firearms during arrest. No injuries.0::480::Adult 18+0::Male0::Sean M. GummowUnknown0::Unharmed, Arrested0::Subject-Suspecthttps://www.kxly.com/news/domestic-violence-suspect-arrested-after-swat-team-standoff/7235252754.04.0
23967210831422018-03-31LouisianaRayneNorth Riceland Road and Highway 9000http://www.gunviolencearchive.org/incident/1083142http://www.klfy.com/news/local/rayne-woman-charged-with-attemped-murder-for-shooting-at-victim-trying-to-visit-children/1094165597False2.00::Unknown0::UnknownShots Fired - No Injuries30.527237Unknown-91.1022631.0No Notes0::250::Adult 18+0::Female0::Jhkeya TezenoUnknown0::Unharmed, Arrested0::Subject-Suspecthttp://www.klfy.com/news/local/rayne-woman-charged-with-attemped-murder-for-shooting-at-victim-trying-to-visit-children/109416559793.05.0
23967310831392018-03-31LouisianaNatchitoches247 Keyser Ave10http://www.gunviolencearchive.org/incident/1083139http://www.ksla.com/story/37854648/man-wanted-in-connection-with-natchitoches-parish-shooting-surrendersFalse4.00::Unknown0::UnknownShot - Dead (murder, accidental, suicide)||Institution/Group/Business31.753700Shop Rite-93.0836001.0No Notes1::210::Adult 18+||1::Adult 18+0::Male||1::Male0::Jamal Haskett||1::Jaquarious Tyjuan ArdisonUnknown0::Killed||1::Unharmed, Arrested0::Victim||1::Subject-Suspecthttp://www.ksla.com/story/37854648/man-wanted-in-connection-with-natchitoches-parish-shooting-surrenders23.031.0
23967410831512018-03-31LouisianaGretna1300 block of Cook Street01http://www.gunviolencearchive.org/incident/1083151http://www.nola.com/crime/index.ssf/2018/04/shooting_reported_on_st_charle.html#incart_river_indexFalse2.00::Unknown0::UnknownShot - Wounded/Injured29.923900Unknown-90.0442001.0No Notes0::210::Adult 18+0::MaleUnknownUnknown0::Injured0::Victimhttp://www.nola.com/crime/index.ssf/2018/04/shooting_reported_on_st_charle.html#incart_river_index85.07.0
23967510825142018-03-31TexasHouston12630 Ashford Point Dr10http://www.gunviolencearchive.org/incident/1082514https://www.chron.com/news/houston-texas/houston/article/Man-found-shot-in-car-in-Houston-s-Westside-12799287.phpFalse9.00::Unknown0::UnknownShot - Dead (murder, accidental, suicide)29.720100Vanderbilt Court apartments-95.6110001.0Vic was found shot to death in car on 4/1/18, apartment complex0::420::Adult 18+0::Male0::Leroy EllisUnknown0::Killed0::Victimhttp://www.khou.com/article/news/hpd-investigating-after-man-found-dead-in-car-on-easter-sunday/285-534039633||https://www.chron.com/news/houston-texas/houston/article/Man-found-shot-in-car-in-Houston-s-Westside-12799287.php149.017.0